1 2 /* 3 Defines the basic matrix operations for sequential dense. 4 */ 5 6 #include <../src/mat/impls/dense/seq/dense.h> /*I "petscmat.h" I*/ 7 #include <petscblaslapack.h> 8 9 #include <../src/mat/impls/aij/seq/aij.h> 10 11 static PetscErrorCode MatSeqDenseSymmetrize_Private(Mat A, PetscBool hermitian) 12 { 13 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 14 PetscInt j, k, n = A->rmap->n; 15 16 PetscFunctionBegin; 17 if (A->rmap->n != A->cmap->n) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Cannot symmetrize a rectangular matrix"); 18 if (!hermitian) { 19 for (k=0;k<n;k++) { 20 for (j=k;j<n;j++) { 21 mat->v[j*mat->lda + k] = mat->v[k*mat->lda + j]; 22 } 23 } 24 } else { 25 for (k=0;k<n;k++) { 26 for (j=k;j<n;j++) { 27 mat->v[j*mat->lda + k] = PetscConj(mat->v[k*mat->lda + j]); 28 } 29 } 30 } 31 PetscFunctionReturn(0); 32 } 33 34 PETSC_EXTERN PetscErrorCode MatSeqDenseInvertFactors_Private(Mat A) 35 { 36 #if defined(PETSC_MISSING_LAPACK_POTRF) 37 PetscFunctionBegin; 38 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"POTRF - Lapack routine is unavailable."); 39 #else 40 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 41 PetscErrorCode ierr; 42 PetscBLASInt info,n; 43 44 PetscFunctionBegin; 45 if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(0); 46 ierr = PetscBLASIntCast(A->cmap->n,&n);CHKERRQ(ierr); 47 if (A->factortype == MAT_FACTOR_LU) { 48 if (!mat->pivots) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Pivots not present"); 49 if (!mat->fwork) { 50 mat->lfwork = n; 51 ierr = PetscMalloc1(mat->lfwork,&mat->fwork);CHKERRQ(ierr); 52 ierr = PetscLogObjectMemory((PetscObject)A,mat->lfwork*sizeof(PetscBLASInt));CHKERRQ(ierr); 53 } 54 PetscStackCallBLAS("LAPACKgetri",LAPACKgetri_(&n,mat->v,&mat->lda,mat->pivots,mat->fwork,&mat->lfwork,&info)); 55 ierr = PetscLogFlops((1.0*A->cmap->n*A->cmap->n*A->cmap->n)/3.0);CHKERRQ(ierr); /* TODO CHECK FLOPS */ 56 } else if (A->factortype == MAT_FACTOR_CHOLESKY) { 57 if (A->spd) { 58 PetscStackCallBLAS("LAPACKpotri",LAPACKpotri_("L",&n,mat->v,&mat->lda,&info)); 59 ierr = MatSeqDenseSymmetrize_Private(A,PETSC_TRUE);CHKERRQ(ierr); 60 #if defined (PETSC_USE_COMPLEX) 61 } else if (A->hermitian) { 62 if (!mat->pivots) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Pivots not present"); 63 if (!mat->fwork) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Fwork not present"); 64 PetscStackCallBLAS("LAPACKhetri",LAPACKhetri_("L",&n,mat->v,&mat->lda,mat->pivots,mat->fwork,&info)); 65 ierr = MatSeqDenseSymmetrize_Private(A,PETSC_TRUE);CHKERRQ(ierr); 66 #endif 67 } else { /* symmetric case */ 68 if (!mat->pivots) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Pivots not present"); 69 if (!mat->fwork) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Fwork not present"); 70 PetscStackCallBLAS("LAPACKsytri",LAPACKsytri_("L",&n,mat->v,&mat->lda,mat->pivots,mat->fwork,&info)); 71 ierr = MatSeqDenseSymmetrize_Private(A,PETSC_FALSE);CHKERRQ(ierr); 72 } 73 if (info) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_MAT_CH_ZRPVT,"Bad Inversion: zero pivot in row %D",(PetscInt)info-1); 74 ierr = PetscLogFlops((1.0*A->cmap->n*A->cmap->n*A->cmap->n)/3.0);CHKERRQ(ierr); /* TODO CHECK FLOPS */ 75 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix must be factored to solve"); 76 #endif 77 78 A->ops->solve = NULL; 79 A->ops->matsolve = NULL; 80 A->ops->solvetranspose = NULL; 81 A->ops->matsolvetranspose = NULL; 82 A->ops->solveadd = NULL; 83 A->ops->solvetransposeadd = NULL; 84 A->factortype = MAT_FACTOR_NONE; 85 ierr = PetscFree(A->solvertype);CHKERRQ(ierr); 86 PetscFunctionReturn(0); 87 } 88 89 PetscErrorCode MatZeroRowsColumns_SeqDense(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 90 { 91 PetscErrorCode ierr; 92 Mat_SeqDense *l = (Mat_SeqDense*)A->data; 93 PetscInt m = l->lda, n = A->cmap->n,r = A->rmap->n, i,j; 94 PetscScalar *slot,*bb; 95 const PetscScalar *xx; 96 97 PetscFunctionBegin; 98 #if defined(PETSC_USE_DEBUG) 99 for (i=0; i<N; i++) { 100 if (rows[i] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row requested to be zeroed"); 101 if (rows[i] >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D requested to be zeroed greater than or equal number of rows %D",rows[i],A->rmap->n); 102 if (rows[i] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Col %D requested to be zeroed greater than or equal number of cols %D",rows[i],A->cmap->n); 103 } 104 #endif 105 106 /* fix right hand side if needed */ 107 if (x && b) { 108 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 109 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 110 for (i=0; i<N; i++) bb[rows[i]] = diag*xx[rows[i]]; 111 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 112 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 113 } 114 115 for (i=0; i<N; i++) { 116 slot = l->v + rows[i]*m; 117 ierr = PetscMemzero(slot,r*sizeof(PetscScalar));CHKERRQ(ierr); 118 } 119 for (i=0; i<N; i++) { 120 slot = l->v + rows[i]; 121 for (j=0; j<n; j++) { *slot = 0.0; slot += m;} 122 } 123 if (diag != 0.0) { 124 if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only coded for square matrices"); 125 for (i=0; i<N; i++) { 126 slot = l->v + (m+1)*rows[i]; 127 *slot = diag; 128 } 129 } 130 PetscFunctionReturn(0); 131 } 132 133 PetscErrorCode MatPtAPNumeric_SeqDense_SeqDense(Mat A,Mat P,Mat C) 134 { 135 Mat_SeqDense *c = (Mat_SeqDense*)(C->data); 136 PetscErrorCode ierr; 137 138 PetscFunctionBegin; 139 ierr = MatMatMultNumeric_SeqDense_SeqDense(A,P,c->ptapwork);CHKERRQ(ierr); 140 ierr = MatTransposeMatMultNumeric_SeqDense_SeqDense(P,c->ptapwork,C);CHKERRQ(ierr); 141 PetscFunctionReturn(0); 142 } 143 144 PetscErrorCode MatPtAPSymbolic_SeqDense_SeqDense(Mat A,Mat P,PetscReal fill,Mat *C) 145 { 146 Mat_SeqDense *c; 147 PetscErrorCode ierr; 148 149 PetscFunctionBegin; 150 ierr = MatCreateSeqDense(PetscObjectComm((PetscObject)A),P->cmap->N,P->cmap->N,NULL,C);CHKERRQ(ierr); 151 c = (Mat_SeqDense*)((*C)->data); 152 ierr = MatCreateSeqDense(PetscObjectComm((PetscObject)A),A->rmap->N,P->cmap->N,NULL,&c->ptapwork);CHKERRQ(ierr); 153 PetscFunctionReturn(0); 154 } 155 156 PETSC_INTERN PetscErrorCode MatPtAP_SeqDense_SeqDense(Mat A,Mat P,MatReuse reuse,PetscReal fill,Mat *C) 157 { 158 PetscErrorCode ierr; 159 160 PetscFunctionBegin; 161 if (reuse == MAT_INITIAL_MATRIX) { 162 ierr = MatPtAPSymbolic_SeqDense_SeqDense(A,P,fill,C);CHKERRQ(ierr); 163 } 164 ierr = PetscLogEventBegin(MAT_PtAPNumeric,A,P,0,0);CHKERRQ(ierr); 165 ierr = (*(*C)->ops->ptapnumeric)(A,P,*C);CHKERRQ(ierr); 166 ierr = PetscLogEventEnd(MAT_PtAPNumeric,A,P,0,0);CHKERRQ(ierr); 167 PetscFunctionReturn(0); 168 } 169 170 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqDense(Mat A,MatType newtype,MatReuse reuse,Mat *newmat) 171 { 172 Mat B = NULL; 173 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 174 Mat_SeqDense *b; 175 PetscErrorCode ierr; 176 PetscInt *ai=a->i,*aj=a->j,m=A->rmap->N,n=A->cmap->N,i; 177 MatScalar *av=a->a; 178 PetscBool isseqdense; 179 180 PetscFunctionBegin; 181 if (reuse == MAT_REUSE_MATRIX) { 182 ierr = PetscObjectTypeCompare((PetscObject)*newmat,MATSEQDENSE,&isseqdense);CHKERRQ(ierr); 183 if (!isseqdense) SETERRQ1(PetscObjectComm((PetscObject)*newmat),PETSC_ERR_USER,"Cannot reuse matrix of type %s",((PetscObject)(*newmat))->type); 184 } 185 if (reuse != MAT_REUSE_MATRIX) { 186 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 187 ierr = MatSetSizes(B,m,n,m,n);CHKERRQ(ierr); 188 ierr = MatSetType(B,MATSEQDENSE);CHKERRQ(ierr); 189 ierr = MatSeqDenseSetPreallocation(B,NULL);CHKERRQ(ierr); 190 b = (Mat_SeqDense*)(B->data); 191 } else { 192 b = (Mat_SeqDense*)((*newmat)->data); 193 ierr = PetscMemzero(b->v,m*n*sizeof(PetscScalar));CHKERRQ(ierr); 194 } 195 for (i=0; i<m; i++) { 196 PetscInt j; 197 for (j=0;j<ai[1]-ai[0];j++) { 198 b->v[*aj*m+i] = *av; 199 aj++; 200 av++; 201 } 202 ai++; 203 } 204 205 if (reuse == MAT_INPLACE_MATRIX) { 206 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 207 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 208 ierr = MatHeaderReplace(A,&B);CHKERRQ(ierr); 209 } else { 210 if (B) *newmat = B; 211 ierr = MatAssemblyBegin(*newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 212 ierr = MatAssemblyEnd(*newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 213 } 214 PetscFunctionReturn(0); 215 } 216 217 PETSC_INTERN PetscErrorCode MatConvert_SeqDense_SeqAIJ(Mat A, MatType newtype,MatReuse reuse,Mat *newmat) 218 { 219 Mat B; 220 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 221 PetscErrorCode ierr; 222 PetscInt i, j; 223 PetscInt *rows, *nnz; 224 MatScalar *aa = a->v, *vals; 225 226 PetscFunctionBegin; 227 ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr); 228 ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 229 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 230 ierr = PetscCalloc3(A->rmap->n,&rows,A->rmap->n,&nnz,A->rmap->n,&vals);CHKERRQ(ierr); 231 for (j=0; j<A->cmap->n; j++) { 232 for (i=0; i<A->rmap->n; i++) if (aa[i] != 0.0 || i == j) ++nnz[i]; 233 aa += a->lda; 234 } 235 ierr = MatSeqAIJSetPreallocation(B,PETSC_DETERMINE,nnz);CHKERRQ(ierr); 236 aa = a->v; 237 for (j=0; j<A->cmap->n; j++) { 238 PetscInt numRows = 0; 239 for (i=0; i<A->rmap->n; i++) if (aa[i] != 0.0 || i == j) {rows[numRows] = i; vals[numRows++] = aa[i];} 240 ierr = MatSetValues(B,numRows,rows,1,&j,vals,INSERT_VALUES);CHKERRQ(ierr); 241 aa += a->lda; 242 } 243 ierr = PetscFree3(rows,nnz,vals);CHKERRQ(ierr); 244 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 245 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 246 247 if (reuse == MAT_INPLACE_MATRIX) { 248 ierr = MatHeaderReplace(A,&B);CHKERRQ(ierr); 249 } else { 250 *newmat = B; 251 } 252 PetscFunctionReturn(0); 253 } 254 255 static PetscErrorCode MatAXPY_SeqDense(Mat Y,PetscScalar alpha,Mat X,MatStructure str) 256 { 257 Mat_SeqDense *x = (Mat_SeqDense*)X->data,*y = (Mat_SeqDense*)Y->data; 258 PetscScalar oalpha = alpha; 259 PetscInt j; 260 PetscBLASInt N,m,ldax,lday,one = 1; 261 PetscErrorCode ierr; 262 263 PetscFunctionBegin; 264 ierr = PetscBLASIntCast(X->rmap->n*X->cmap->n,&N);CHKERRQ(ierr); 265 ierr = PetscBLASIntCast(X->rmap->n,&m);CHKERRQ(ierr); 266 ierr = PetscBLASIntCast(x->lda,&ldax);CHKERRQ(ierr); 267 ierr = PetscBLASIntCast(y->lda,&lday);CHKERRQ(ierr); 268 if (ldax>m || lday>m) { 269 for (j=0; j<X->cmap->n; j++) { 270 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&m,&oalpha,x->v+j*ldax,&one,y->v+j*lday,&one)); 271 } 272 } else { 273 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&N,&oalpha,x->v,&one,y->v,&one)); 274 } 275 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 276 ierr = PetscLogFlops(PetscMax(2*N-1,0));CHKERRQ(ierr); 277 PetscFunctionReturn(0); 278 } 279 280 static PetscErrorCode MatGetInfo_SeqDense(Mat A,MatInfoType flag,MatInfo *info) 281 { 282 PetscInt N = A->rmap->n*A->cmap->n; 283 284 PetscFunctionBegin; 285 info->block_size = 1.0; 286 info->nz_allocated = (double)N; 287 info->nz_used = (double)N; 288 info->nz_unneeded = (double)0; 289 info->assemblies = (double)A->num_ass; 290 info->mallocs = 0; 291 info->memory = ((PetscObject)A)->mem; 292 info->fill_ratio_given = 0; 293 info->fill_ratio_needed = 0; 294 info->factor_mallocs = 0; 295 PetscFunctionReturn(0); 296 } 297 298 static PetscErrorCode MatScale_SeqDense(Mat A,PetscScalar alpha) 299 { 300 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 301 PetscScalar oalpha = alpha; 302 PetscErrorCode ierr; 303 PetscBLASInt one = 1,j,nz,lda; 304 305 PetscFunctionBegin; 306 ierr = PetscBLASIntCast(a->lda,&lda);CHKERRQ(ierr); 307 if (lda>A->rmap->n) { 308 ierr = PetscBLASIntCast(A->rmap->n,&nz);CHKERRQ(ierr); 309 for (j=0; j<A->cmap->n; j++) { 310 PetscStackCallBLAS("BLASscal",BLASscal_(&nz,&oalpha,a->v+j*lda,&one)); 311 } 312 } else { 313 ierr = PetscBLASIntCast(A->rmap->n*A->cmap->n,&nz);CHKERRQ(ierr); 314 PetscStackCallBLAS("BLASscal",BLASscal_(&nz,&oalpha,a->v,&one)); 315 } 316 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 317 PetscFunctionReturn(0); 318 } 319 320 static PetscErrorCode MatIsHermitian_SeqDense(Mat A,PetscReal rtol,PetscBool *fl) 321 { 322 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 323 PetscInt i,j,m = A->rmap->n,N; 324 PetscScalar *v = a->v; 325 326 PetscFunctionBegin; 327 *fl = PETSC_FALSE; 328 if (A->rmap->n != A->cmap->n) PetscFunctionReturn(0); 329 N = a->lda; 330 331 for (i=0; i<m; i++) { 332 for (j=i+1; j<m; j++) { 333 if (PetscAbsScalar(v[i+j*N] - PetscConj(v[j+i*N])) > rtol) PetscFunctionReturn(0); 334 } 335 } 336 *fl = PETSC_TRUE; 337 PetscFunctionReturn(0); 338 } 339 340 static PetscErrorCode MatDuplicateNoCreate_SeqDense(Mat newi,Mat A,MatDuplicateOption cpvalues) 341 { 342 Mat_SeqDense *mat = (Mat_SeqDense*)A->data,*l; 343 PetscErrorCode ierr; 344 PetscInt lda = (PetscInt)mat->lda,j,m; 345 346 PetscFunctionBegin; 347 ierr = PetscLayoutReference(A->rmap,&newi->rmap);CHKERRQ(ierr); 348 ierr = PetscLayoutReference(A->cmap,&newi->cmap);CHKERRQ(ierr); 349 ierr = MatSeqDenseSetPreallocation(newi,NULL);CHKERRQ(ierr); 350 if (cpvalues == MAT_COPY_VALUES) { 351 l = (Mat_SeqDense*)newi->data; 352 if (lda>A->rmap->n) { 353 m = A->rmap->n; 354 for (j=0; j<A->cmap->n; j++) { 355 ierr = PetscMemcpy(l->v+j*m,mat->v+j*lda,m*sizeof(PetscScalar));CHKERRQ(ierr); 356 } 357 } else { 358 ierr = PetscMemcpy(l->v,mat->v,A->rmap->n*A->cmap->n*sizeof(PetscScalar));CHKERRQ(ierr); 359 } 360 } 361 newi->assembled = PETSC_TRUE; 362 PetscFunctionReturn(0); 363 } 364 365 static PetscErrorCode MatDuplicate_SeqDense(Mat A,MatDuplicateOption cpvalues,Mat *newmat) 366 { 367 PetscErrorCode ierr; 368 369 PetscFunctionBegin; 370 ierr = MatCreate(PetscObjectComm((PetscObject)A),newmat);CHKERRQ(ierr); 371 ierr = MatSetSizes(*newmat,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 372 ierr = MatSetType(*newmat,((PetscObject)A)->type_name);CHKERRQ(ierr); 373 ierr = MatDuplicateNoCreate_SeqDense(*newmat,A,cpvalues);CHKERRQ(ierr); 374 PetscFunctionReturn(0); 375 } 376 377 378 static PetscErrorCode MatLUFactor_SeqDense(Mat,IS,IS,const MatFactorInfo*); 379 380 static PetscErrorCode MatLUFactorNumeric_SeqDense(Mat fact,Mat A,const MatFactorInfo *info_dummy) 381 { 382 MatFactorInfo info; 383 PetscErrorCode ierr; 384 385 PetscFunctionBegin; 386 ierr = MatDuplicateNoCreate_SeqDense(fact,A,MAT_COPY_VALUES);CHKERRQ(ierr); 387 ierr = MatLUFactor_SeqDense(fact,0,0,&info);CHKERRQ(ierr); 388 PetscFunctionReturn(0); 389 } 390 391 static PetscErrorCode MatSolve_SeqDense(Mat A,Vec xx,Vec yy) 392 { 393 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 394 PetscErrorCode ierr; 395 const PetscScalar *x; 396 PetscScalar *y; 397 PetscBLASInt one = 1,info,m; 398 399 PetscFunctionBegin; 400 ierr = PetscBLASIntCast(A->rmap->n,&m);CHKERRQ(ierr); 401 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 402 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 403 ierr = PetscMemcpy(y,x,A->rmap->n*sizeof(PetscScalar));CHKERRQ(ierr); 404 if (A->factortype == MAT_FACTOR_LU) { 405 #if defined(PETSC_MISSING_LAPACK_GETRS) 406 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GETRS - Lapack routine is unavailable."); 407 #else 408 PetscStackCallBLAS("LAPACKgetrs",LAPACKgetrs_("N",&m,&one,mat->v,&mat->lda,mat->pivots,y,&m,&info)); 409 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"GETRS - Bad solve"); 410 #endif 411 } else if (A->factortype == MAT_FACTOR_CHOLESKY) { 412 #if defined(PETSC_MISSING_LAPACK_POTRS) 413 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"POTRS - Lapack routine is unavailable."); 414 #else 415 if (A->spd) { 416 PetscStackCallBLAS("LAPACKpotrs",LAPACKpotrs_("L",&m,&one,mat->v,&mat->lda,y,&m,&info)); 417 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"POTRS Bad solve"); 418 #if defined (PETSC_USE_COMPLEX) 419 } else if (A->hermitian) { 420 PetscStackCallBLAS("LAPACKhetrs",LAPACKhetrs_("L",&m,&one,mat->v,&mat->lda,mat->pivots,y,&m,&info)); 421 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"HETRS Bad solve"); 422 #endif 423 } else { /* symmetric case */ 424 PetscStackCallBLAS("LAPACKsytrs",LAPACKsytrs_("L",&m,&one,mat->v,&mat->lda,mat->pivots,y,&m,&info)); 425 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"SYTRS Bad solve"); 426 } 427 #endif 428 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix must be factored to solve"); 429 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 430 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 431 ierr = PetscLogFlops(2.0*A->cmap->n*A->cmap->n - A->cmap->n);CHKERRQ(ierr); 432 PetscFunctionReturn(0); 433 } 434 435 static PetscErrorCode MatMatSolve_SeqDense(Mat A,Mat B,Mat X) 436 { 437 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 438 PetscErrorCode ierr; 439 PetscScalar *b,*x; 440 PetscInt n; 441 PetscBLASInt nrhs,info,m; 442 PetscBool flg; 443 444 PetscFunctionBegin; 445 ierr = PetscBLASIntCast(A->rmap->n,&m);CHKERRQ(ierr); 446 ierr = PetscObjectTypeCompareAny((PetscObject)B,&flg,MATSEQDENSE,MATMPIDENSE,NULL);CHKERRQ(ierr); 447 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix B must be MATDENSE matrix"); 448 ierr = PetscObjectTypeCompareAny((PetscObject)X,&flg,MATSEQDENSE,MATMPIDENSE,NULL);CHKERRQ(ierr); 449 if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Matrix X must be MATDENSE matrix"); 450 451 ierr = MatGetSize(B,NULL,&n);CHKERRQ(ierr); 452 ierr = PetscBLASIntCast(n,&nrhs);CHKERRQ(ierr); 453 ierr = MatDenseGetArray(B,&b);CHKERRQ(ierr); 454 ierr = MatDenseGetArray(X,&x);CHKERRQ(ierr); 455 456 ierr = PetscMemcpy(x,b,m*nrhs*sizeof(PetscScalar));CHKERRQ(ierr); 457 458 if (A->factortype == MAT_FACTOR_LU) { 459 #if defined(PETSC_MISSING_LAPACK_GETRS) 460 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GETRS - Lapack routine is unavailable."); 461 #else 462 PetscStackCallBLAS("LAPACKgetrs",LAPACKgetrs_("N",&m,&nrhs,mat->v,&mat->lda,mat->pivots,x,&m,&info)); 463 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"GETRS - Bad solve"); 464 #endif 465 } else if (A->factortype == MAT_FACTOR_CHOLESKY) { 466 #if defined(PETSC_MISSING_LAPACK_POTRS) 467 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"POTRS - Lapack routine is unavailable."); 468 #else 469 if (A->spd) { 470 PetscStackCallBLAS("LAPACKpotrs",LAPACKpotrs_("L",&m,&nrhs,mat->v,&mat->lda,x,&m,&info)); 471 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"POTRS Bad solve"); 472 #if defined (PETSC_USE_COMPLEX) 473 } else if (A->hermitian) { 474 PetscStackCallBLAS("LAPACKhetrs",LAPACKhetrs_("L",&m,&nrhs,mat->v,&mat->lda,mat->pivots,x,&m,&info)); 475 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"HETRS Bad solve"); 476 #endif 477 } else { /* symmetric case */ 478 PetscStackCallBLAS("LAPACKsytrs",LAPACKsytrs_("L",&m,&nrhs,mat->v,&mat->lda,mat->pivots,x,&m,&info)); 479 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"SYTRS Bad solve"); 480 } 481 #endif 482 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix must be factored to solve"); 483 484 ierr = MatDenseRestoreArray(B,&b);CHKERRQ(ierr); 485 ierr = MatDenseRestoreArray(X,&x);CHKERRQ(ierr); 486 ierr = PetscLogFlops(nrhs*(2.0*m*m - m));CHKERRQ(ierr); 487 PetscFunctionReturn(0); 488 } 489 490 static PetscErrorCode MatSolveTranspose_SeqDense(Mat A,Vec xx,Vec yy) 491 { 492 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 493 PetscErrorCode ierr; 494 const PetscScalar *x; 495 PetscScalar *y; 496 PetscBLASInt one = 1,info,m; 497 498 PetscFunctionBegin; 499 ierr = PetscBLASIntCast(A->rmap->n,&m);CHKERRQ(ierr); 500 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 501 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 502 ierr = PetscMemcpy(y,x,A->rmap->n*sizeof(PetscScalar));CHKERRQ(ierr); 503 if (A->factortype == MAT_FACTOR_LU) { 504 #if defined(PETSC_MISSING_LAPACK_GETRS) 505 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GETRS - Lapack routine is unavailable."); 506 #else 507 PetscStackCallBLAS("LAPACKgetrs",LAPACKgetrs_("T",&m,&one,mat->v,&mat->lda,mat->pivots,y,&m,&info)); 508 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"POTRS - Bad solve"); 509 #endif 510 } else if (A->factortype == MAT_FACTOR_CHOLESKY) { 511 #if defined(PETSC_MISSING_LAPACK_POTRS) 512 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"POTRS - Lapack routine is unavailable."); 513 #else 514 if (A->spd) { 515 PetscStackCallBLAS("LAPACKpotrs",LAPACKpotrs_("L",&m,&one,mat->v,&mat->lda,y,&m,&info)); 516 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"POTRS Bad solve"); 517 #if defined (PETSC_USE_COMPLEX) 518 } else if (A->hermitian) { 519 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSolveTranspose with Cholesky/Hermitian not available"); 520 #endif 521 } else { /* symmetric case */ 522 PetscStackCallBLAS("LAPACKsytrs",LAPACKsytrs_("L",&m,&one,mat->v,&mat->lda,mat->pivots,y,&m,&info)); 523 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"SYTRS Bad solve"); 524 } 525 #endif 526 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix must be factored to solve"); 527 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 528 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 529 ierr = PetscLogFlops(2.0*A->cmap->n*A->cmap->n - A->cmap->n);CHKERRQ(ierr); 530 PetscFunctionReturn(0); 531 } 532 533 static PetscErrorCode MatSolveAdd_SeqDense(Mat A,Vec xx,Vec zz,Vec yy) 534 { 535 PetscErrorCode ierr; 536 const PetscScalar *x; 537 PetscScalar *y,sone = 1.0; 538 Vec tmp = 0; 539 540 PetscFunctionBegin; 541 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 542 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 543 if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(0); 544 if (yy == zz) { 545 ierr = VecDuplicate(yy,&tmp);CHKERRQ(ierr); 546 ierr = PetscLogObjectParent((PetscObject)A,(PetscObject)tmp);CHKERRQ(ierr); 547 ierr = VecCopy(yy,tmp);CHKERRQ(ierr); 548 } 549 ierr = MatSolve_SeqDense(A,xx,yy);CHKERRQ(ierr); 550 if (tmp) { 551 ierr = VecAXPY(yy,sone,tmp);CHKERRQ(ierr); 552 ierr = VecDestroy(&tmp);CHKERRQ(ierr); 553 } else { 554 ierr = VecAXPY(yy,sone,zz);CHKERRQ(ierr); 555 } 556 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 557 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 558 ierr = PetscLogFlops(A->cmap->n);CHKERRQ(ierr); 559 PetscFunctionReturn(0); 560 } 561 562 static PetscErrorCode MatSolveTransposeAdd_SeqDense(Mat A,Vec xx,Vec zz,Vec yy) 563 { 564 PetscErrorCode ierr; 565 const PetscScalar *x; 566 PetscScalar *y,sone = 1.0; 567 Vec tmp = NULL; 568 569 PetscFunctionBegin; 570 if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(0); 571 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 572 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 573 if (yy == zz) { 574 ierr = VecDuplicate(yy,&tmp);CHKERRQ(ierr); 575 ierr = PetscLogObjectParent((PetscObject)A,(PetscObject)tmp);CHKERRQ(ierr); 576 ierr = VecCopy(yy,tmp);CHKERRQ(ierr); 577 } 578 ierr = MatSolveTranspose_SeqDense(A,xx,yy);CHKERRQ(ierr); 579 if (tmp) { 580 ierr = VecAXPY(yy,sone,tmp);CHKERRQ(ierr); 581 ierr = VecDestroy(&tmp);CHKERRQ(ierr); 582 } else { 583 ierr = VecAXPY(yy,sone,zz);CHKERRQ(ierr); 584 } 585 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 586 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 587 ierr = PetscLogFlops(A->cmap->n);CHKERRQ(ierr); 588 PetscFunctionReturn(0); 589 } 590 591 /* ---------------------------------------------------------------*/ 592 /* COMMENT: I have chosen to hide row permutation in the pivots, 593 rather than put it in the Mat->row slot.*/ 594 static PetscErrorCode MatLUFactor_SeqDense(Mat A,IS row,IS col,const MatFactorInfo *minfo) 595 { 596 #if defined(PETSC_MISSING_LAPACK_GETRF) 597 PetscFunctionBegin; 598 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GETRF - Lapack routine is unavailable."); 599 #else 600 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 601 PetscErrorCode ierr; 602 PetscBLASInt n,m,info; 603 604 PetscFunctionBegin; 605 ierr = PetscBLASIntCast(A->cmap->n,&n);CHKERRQ(ierr); 606 ierr = PetscBLASIntCast(A->rmap->n,&m);CHKERRQ(ierr); 607 if (!mat->pivots) { 608 ierr = PetscMalloc1(A->rmap->n,&mat->pivots);CHKERRQ(ierr); 609 ierr = PetscLogObjectMemory((PetscObject)A,A->rmap->n*sizeof(PetscBLASInt));CHKERRQ(ierr); 610 } 611 if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(0); 612 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 613 PetscStackCallBLAS("LAPACKgetrf",LAPACKgetrf_(&m,&n,mat->v,&mat->lda,mat->pivots,&info)); 614 ierr = PetscFPTrapPop();CHKERRQ(ierr); 615 616 if (info<0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"Bad argument to LU factorization"); 617 if (info>0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Bad LU factorization"); 618 619 A->ops->solve = MatSolve_SeqDense; 620 A->ops->matsolve = MatMatSolve_SeqDense; 621 A->ops->solvetranspose = MatSolveTranspose_SeqDense; 622 A->ops->solveadd = MatSolveAdd_SeqDense; 623 A->ops->solvetransposeadd = MatSolveTransposeAdd_SeqDense; 624 A->factortype = MAT_FACTOR_LU; 625 626 ierr = PetscFree(A->solvertype);CHKERRQ(ierr); 627 ierr = PetscStrallocpy(MATSOLVERPETSC,&A->solvertype);CHKERRQ(ierr); 628 629 ierr = PetscLogFlops((2.0*A->cmap->n*A->cmap->n*A->cmap->n)/3);CHKERRQ(ierr); 630 #endif 631 PetscFunctionReturn(0); 632 } 633 634 /* Cholesky as L*L^T or L*D*L^T and the symmetric/hermitian complex variants */ 635 static PetscErrorCode MatCholeskyFactor_SeqDense(Mat A,IS perm,const MatFactorInfo *factinfo) 636 { 637 #if defined(PETSC_MISSING_LAPACK_POTRF) 638 PetscFunctionBegin; 639 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"POTRF - Lapack routine is unavailable."); 640 #else 641 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 642 PetscErrorCode ierr; 643 PetscBLASInt info,n; 644 645 PetscFunctionBegin; 646 ierr = PetscBLASIntCast(A->cmap->n,&n);CHKERRQ(ierr); 647 if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(0); 648 if (A->spd) { 649 PetscStackCallBLAS("LAPACKpotrf",LAPACKpotrf_("L",&n,mat->v,&mat->lda,&info)); 650 #if defined (PETSC_USE_COMPLEX) 651 } else if (A->hermitian) { 652 if (!mat->pivots) { 653 ierr = PetscMalloc1(A->rmap->n,&mat->pivots);CHKERRQ(ierr); 654 ierr = PetscLogObjectMemory((PetscObject)A,A->rmap->n*sizeof(PetscBLASInt));CHKERRQ(ierr); 655 } 656 if (!mat->fwork) { 657 PetscScalar dummy; 658 659 mat->lfwork = -1; 660 PetscStackCallBLAS("LAPACKhetrf",LAPACKhetrf_("L",&n,mat->v,&mat->lda,mat->pivots,&dummy,&mat->lfwork,&info)); 661 mat->lfwork = (PetscInt)PetscRealPart(dummy); 662 ierr = PetscMalloc1(mat->lfwork,&mat->fwork);CHKERRQ(ierr); 663 ierr = PetscLogObjectMemory((PetscObject)A,mat->lfwork*sizeof(PetscBLASInt));CHKERRQ(ierr); 664 } 665 PetscStackCallBLAS("LAPACKhetrf",LAPACKhetrf_("L",&n,mat->v,&mat->lda,mat->pivots,mat->fwork,&mat->lfwork,&info)); 666 #endif 667 } else { /* symmetric case */ 668 if (!mat->pivots) { 669 ierr = PetscMalloc1(A->rmap->n,&mat->pivots);CHKERRQ(ierr); 670 ierr = PetscLogObjectMemory((PetscObject)A,A->rmap->n*sizeof(PetscBLASInt));CHKERRQ(ierr); 671 } 672 if (!mat->fwork) { 673 PetscScalar dummy; 674 675 mat->lfwork = -1; 676 PetscStackCallBLAS("LAPACKsytrf",LAPACKsytrf_("L",&n,mat->v,&mat->lda,mat->pivots,&dummy,&mat->lfwork,&info)); 677 mat->lfwork = (PetscInt)PetscRealPart(dummy); 678 ierr = PetscMalloc1(mat->lfwork,&mat->fwork);CHKERRQ(ierr); 679 ierr = PetscLogObjectMemory((PetscObject)A,mat->lfwork*sizeof(PetscBLASInt));CHKERRQ(ierr); 680 } 681 PetscStackCallBLAS("LAPACKsytrf",LAPACKsytrf_("L",&n,mat->v,&mat->lda,mat->pivots,mat->fwork,&mat->lfwork,&info)); 682 } 683 if (info) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_MAT_CH_ZRPVT,"Bad factorization: zero pivot in row %D",(PetscInt)info-1); 684 685 A->ops->solve = MatSolve_SeqDense; 686 A->ops->matsolve = MatMatSolve_SeqDense; 687 A->ops->solvetranspose = MatSolveTranspose_SeqDense; 688 A->ops->solveadd = MatSolveAdd_SeqDense; 689 A->ops->solvetransposeadd = MatSolveTransposeAdd_SeqDense; 690 A->factortype = MAT_FACTOR_CHOLESKY; 691 692 ierr = PetscFree(A->solvertype);CHKERRQ(ierr); 693 ierr = PetscStrallocpy(MATSOLVERPETSC,&A->solvertype);CHKERRQ(ierr); 694 695 ierr = PetscLogFlops((1.0*A->cmap->n*A->cmap->n*A->cmap->n)/3.0);CHKERRQ(ierr); 696 #endif 697 PetscFunctionReturn(0); 698 } 699 700 701 PetscErrorCode MatCholeskyFactorNumeric_SeqDense(Mat fact,Mat A,const MatFactorInfo *info_dummy) 702 { 703 PetscErrorCode ierr; 704 MatFactorInfo info; 705 706 PetscFunctionBegin; 707 info.fill = 1.0; 708 709 ierr = MatDuplicateNoCreate_SeqDense(fact,A,MAT_COPY_VALUES);CHKERRQ(ierr); 710 ierr = MatCholeskyFactor_SeqDense(fact,0,&info);CHKERRQ(ierr); 711 PetscFunctionReturn(0); 712 } 713 714 static PetscErrorCode MatCholeskyFactorSymbolic_SeqDense(Mat fact,Mat A,IS row,const MatFactorInfo *info) 715 { 716 PetscFunctionBegin; 717 fact->assembled = PETSC_TRUE; 718 fact->preallocated = PETSC_TRUE; 719 fact->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqDense; 720 fact->ops->solve = MatSolve_SeqDense; 721 fact->ops->matsolve = MatMatSolve_SeqDense; 722 fact->ops->solvetranspose = MatSolveTranspose_SeqDense; 723 fact->ops->solveadd = MatSolveAdd_SeqDense; 724 fact->ops->solvetransposeadd = MatSolveTransposeAdd_SeqDense; 725 PetscFunctionReturn(0); 726 } 727 728 static PetscErrorCode MatLUFactorSymbolic_SeqDense(Mat fact,Mat A,IS row,IS col,const MatFactorInfo *info) 729 { 730 PetscFunctionBegin; 731 fact->preallocated = PETSC_TRUE; 732 fact->assembled = PETSC_TRUE; 733 fact->ops->lufactornumeric = MatLUFactorNumeric_SeqDense; 734 fact->ops->solve = MatSolve_SeqDense; 735 fact->ops->matsolve = MatMatSolve_SeqDense; 736 fact->ops->solvetranspose = MatSolveTranspose_SeqDense; 737 fact->ops->solveadd = MatSolveAdd_SeqDense; 738 fact->ops->solvetransposeadd = MatSolveTransposeAdd_SeqDense; 739 PetscFunctionReturn(0); 740 } 741 742 PETSC_INTERN PetscErrorCode MatGetFactor_seqdense_petsc(Mat A,MatFactorType ftype,Mat *fact) 743 { 744 PetscErrorCode ierr; 745 746 PetscFunctionBegin; 747 ierr = MatCreate(PetscObjectComm((PetscObject)A),fact);CHKERRQ(ierr); 748 ierr = MatSetSizes(*fact,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 749 ierr = MatSetType(*fact,((PetscObject)A)->type_name);CHKERRQ(ierr); 750 if (ftype == MAT_FACTOR_LU) { 751 (*fact)->ops->lufactorsymbolic = MatLUFactorSymbolic_SeqDense; 752 } else { 753 (*fact)->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SeqDense; 754 } 755 (*fact)->factortype = ftype; 756 757 ierr = PetscFree((*fact)->solvertype);CHKERRQ(ierr); 758 ierr = PetscStrallocpy(MATSOLVERPETSC,&(*fact)->solvertype);CHKERRQ(ierr); 759 PetscFunctionReturn(0); 760 } 761 762 /* ------------------------------------------------------------------*/ 763 static PetscErrorCode MatSOR_SeqDense(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal shift,PetscInt its,PetscInt lits,Vec xx) 764 { 765 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 766 PetscScalar *x,*v = mat->v,zero = 0.0,xt; 767 const PetscScalar *b; 768 PetscErrorCode ierr; 769 PetscInt m = A->rmap->n,i; 770 PetscBLASInt o = 1,bm; 771 772 PetscFunctionBegin; 773 if (shift == -1) shift = 0.0; /* negative shift indicates do not error on zero diagonal; this code never zeros on zero diagonal */ 774 ierr = PetscBLASIntCast(m,&bm);CHKERRQ(ierr); 775 if (flag & SOR_ZERO_INITIAL_GUESS) { 776 /* this is a hack fix, should have another version without the second BLASdot */ 777 ierr = VecSet(xx,zero);CHKERRQ(ierr); 778 } 779 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 780 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 781 its = its*lits; 782 if (its <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 783 while (its--) { 784 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 785 for (i=0; i<m; i++) { 786 PetscStackCallBLAS("BLASdot",xt = b[i] - BLASdot_(&bm,v+i,&bm,x,&o)); 787 x[i] = (1. - omega)*x[i] + omega*(xt+v[i + i*m]*x[i])/(v[i + i*m]+shift); 788 } 789 } 790 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 791 for (i=m-1; i>=0; i--) { 792 PetscStackCallBLAS("BLASdot",xt = b[i] - BLASdot_(&bm,v+i,&bm,x,&o)); 793 x[i] = (1. - omega)*x[i] + omega*(xt+v[i + i*m]*x[i])/(v[i + i*m]+shift); 794 } 795 } 796 } 797 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 798 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 799 PetscFunctionReturn(0); 800 } 801 802 /* -----------------------------------------------------------------*/ 803 PETSC_INTERN PetscErrorCode MatMultTranspose_SeqDense(Mat A,Vec xx,Vec yy) 804 { 805 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 806 const PetscScalar *v = mat->v,*x; 807 PetscScalar *y; 808 PetscErrorCode ierr; 809 PetscBLASInt m, n,_One=1; 810 PetscScalar _DOne=1.0,_DZero=0.0; 811 812 PetscFunctionBegin; 813 ierr = PetscBLASIntCast(A->rmap->n,&m);CHKERRQ(ierr); 814 ierr = PetscBLASIntCast(A->cmap->n,&n);CHKERRQ(ierr); 815 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 816 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 817 if (!A->rmap->n || !A->cmap->n) { 818 PetscBLASInt i; 819 for (i=0; i<n; i++) y[i] = 0.0; 820 } else { 821 PetscStackCallBLAS("BLASgemv",BLASgemv_("T",&m,&n,&_DOne,v,&mat->lda,x,&_One,&_DZero,y,&_One)); 822 ierr = PetscLogFlops(2.0*A->rmap->n*A->cmap->n - A->cmap->n);CHKERRQ(ierr); 823 } 824 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 825 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 826 PetscFunctionReturn(0); 827 } 828 829 PETSC_INTERN PetscErrorCode MatMult_SeqDense(Mat A,Vec xx,Vec yy) 830 { 831 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 832 PetscScalar *y,_DOne=1.0,_DZero=0.0; 833 PetscErrorCode ierr; 834 PetscBLASInt m, n, _One=1; 835 const PetscScalar *v = mat->v,*x; 836 837 PetscFunctionBegin; 838 ierr = PetscBLASIntCast(A->rmap->n,&m);CHKERRQ(ierr); 839 ierr = PetscBLASIntCast(A->cmap->n,&n);CHKERRQ(ierr); 840 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 841 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 842 if (!A->rmap->n || !A->cmap->n) { 843 PetscBLASInt i; 844 for (i=0; i<m; i++) y[i] = 0.0; 845 } else { 846 PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&m,&n,&_DOne,v,&(mat->lda),x,&_One,&_DZero,y,&_One)); 847 ierr = PetscLogFlops(2.0*A->rmap->n*A->cmap->n - A->rmap->n);CHKERRQ(ierr); 848 } 849 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 850 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 851 PetscFunctionReturn(0); 852 } 853 854 PETSC_INTERN PetscErrorCode MatMultAdd_SeqDense(Mat A,Vec xx,Vec zz,Vec yy) 855 { 856 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 857 const PetscScalar *v = mat->v,*x; 858 PetscScalar *y,_DOne=1.0; 859 PetscErrorCode ierr; 860 PetscBLASInt m, n, _One=1; 861 862 PetscFunctionBegin; 863 ierr = PetscBLASIntCast(A->rmap->n,&m);CHKERRQ(ierr); 864 ierr = PetscBLASIntCast(A->cmap->n,&n);CHKERRQ(ierr); 865 if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(0); 866 if (zz != yy) {ierr = VecCopy(zz,yy);CHKERRQ(ierr);} 867 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 868 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 869 PetscStackCallBLAS("BLASgemv",BLASgemv_("N",&m,&n,&_DOne,v,&(mat->lda),x,&_One,&_DOne,y,&_One)); 870 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 871 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 872 ierr = PetscLogFlops(2.0*A->rmap->n*A->cmap->n);CHKERRQ(ierr); 873 PetscFunctionReturn(0); 874 } 875 876 static PetscErrorCode MatMultTransposeAdd_SeqDense(Mat A,Vec xx,Vec zz,Vec yy) 877 { 878 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 879 const PetscScalar *v = mat->v,*x; 880 PetscScalar *y; 881 PetscErrorCode ierr; 882 PetscBLASInt m, n, _One=1; 883 PetscScalar _DOne=1.0; 884 885 PetscFunctionBegin; 886 ierr = PetscBLASIntCast(A->rmap->n,&m);CHKERRQ(ierr); 887 ierr = PetscBLASIntCast(A->cmap->n,&n);CHKERRQ(ierr); 888 if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(0); 889 if (zz != yy) {ierr = VecCopy(zz,yy);CHKERRQ(ierr);} 890 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 891 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 892 PetscStackCallBLAS("BLASgemv",BLASgemv_("T",&m,&n,&_DOne,v,&(mat->lda),x,&_One,&_DOne,y,&_One)); 893 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 894 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 895 ierr = PetscLogFlops(2.0*A->rmap->n*A->cmap->n);CHKERRQ(ierr); 896 PetscFunctionReturn(0); 897 } 898 899 /* -----------------------------------------------------------------*/ 900 static PetscErrorCode MatGetRow_SeqDense(Mat A,PetscInt row,PetscInt *ncols,PetscInt **cols,PetscScalar **vals) 901 { 902 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 903 PetscScalar *v; 904 PetscErrorCode ierr; 905 PetscInt i; 906 907 PetscFunctionBegin; 908 *ncols = A->cmap->n; 909 if (cols) { 910 ierr = PetscMalloc1(A->cmap->n+1,cols);CHKERRQ(ierr); 911 for (i=0; i<A->cmap->n; i++) (*cols)[i] = i; 912 } 913 if (vals) { 914 ierr = PetscMalloc1(A->cmap->n+1,vals);CHKERRQ(ierr); 915 v = mat->v + row; 916 for (i=0; i<A->cmap->n; i++) {(*vals)[i] = *v; v += mat->lda;} 917 } 918 PetscFunctionReturn(0); 919 } 920 921 static PetscErrorCode MatRestoreRow_SeqDense(Mat A,PetscInt row,PetscInt *ncols,PetscInt **cols,PetscScalar **vals) 922 { 923 PetscErrorCode ierr; 924 925 PetscFunctionBegin; 926 if (cols) {ierr = PetscFree(*cols);CHKERRQ(ierr);} 927 if (vals) {ierr = PetscFree(*vals);CHKERRQ(ierr); } 928 PetscFunctionReturn(0); 929 } 930 /* ----------------------------------------------------------------*/ 931 static PetscErrorCode MatSetValues_SeqDense(Mat A,PetscInt m,const PetscInt indexm[],PetscInt n,const PetscInt indexn[],const PetscScalar v[],InsertMode addv) 932 { 933 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 934 PetscInt i,j,idx=0; 935 936 PetscFunctionBegin; 937 if (!mat->roworiented) { 938 if (addv == INSERT_VALUES) { 939 for (j=0; j<n; j++) { 940 if (indexn[j] < 0) {idx += m; continue;} 941 #if defined(PETSC_USE_DEBUG) 942 if (indexn[j] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",indexn[j],A->cmap->n-1); 943 #endif 944 for (i=0; i<m; i++) { 945 if (indexm[i] < 0) {idx++; continue;} 946 #if defined(PETSC_USE_DEBUG) 947 if (indexm[i] >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",indexm[i],A->rmap->n-1); 948 #endif 949 mat->v[indexn[j]*mat->lda + indexm[i]] = v[idx++]; 950 } 951 } 952 } else { 953 for (j=0; j<n; j++) { 954 if (indexn[j] < 0) {idx += m; continue;} 955 #if defined(PETSC_USE_DEBUG) 956 if (indexn[j] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",indexn[j],A->cmap->n-1); 957 #endif 958 for (i=0; i<m; i++) { 959 if (indexm[i] < 0) {idx++; continue;} 960 #if defined(PETSC_USE_DEBUG) 961 if (indexm[i] >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",indexm[i],A->rmap->n-1); 962 #endif 963 mat->v[indexn[j]*mat->lda + indexm[i]] += v[idx++]; 964 } 965 } 966 } 967 } else { 968 if (addv == INSERT_VALUES) { 969 for (i=0; i<m; i++) { 970 if (indexm[i] < 0) { idx += n; continue;} 971 #if defined(PETSC_USE_DEBUG) 972 if (indexm[i] >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",indexm[i],A->rmap->n-1); 973 #endif 974 for (j=0; j<n; j++) { 975 if (indexn[j] < 0) { idx++; continue;} 976 #if defined(PETSC_USE_DEBUG) 977 if (indexn[j] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",indexn[j],A->cmap->n-1); 978 #endif 979 mat->v[indexn[j]*mat->lda + indexm[i]] = v[idx++]; 980 } 981 } 982 } else { 983 for (i=0; i<m; i++) { 984 if (indexm[i] < 0) { idx += n; continue;} 985 #if defined(PETSC_USE_DEBUG) 986 if (indexm[i] >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",indexm[i],A->rmap->n-1); 987 #endif 988 for (j=0; j<n; j++) { 989 if (indexn[j] < 0) { idx++; continue;} 990 #if defined(PETSC_USE_DEBUG) 991 if (indexn[j] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",indexn[j],A->cmap->n-1); 992 #endif 993 mat->v[indexn[j]*mat->lda + indexm[i]] += v[idx++]; 994 } 995 } 996 } 997 } 998 PetscFunctionReturn(0); 999 } 1000 1001 static PetscErrorCode MatGetValues_SeqDense(Mat A,PetscInt m,const PetscInt indexm[],PetscInt n,const PetscInt indexn[],PetscScalar v[]) 1002 { 1003 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1004 PetscInt i,j; 1005 1006 PetscFunctionBegin; 1007 /* row-oriented output */ 1008 for (i=0; i<m; i++) { 1009 if (indexm[i] < 0) {v += n;continue;} 1010 if (indexm[i] >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D requested larger than number rows %D",indexm[i],A->rmap->n); 1011 for (j=0; j<n; j++) { 1012 if (indexn[j] < 0) {v++; continue;} 1013 if (indexn[j] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column %D requested larger than number columns %D",indexn[j],A->cmap->n); 1014 *v++ = mat->v[indexn[j]*mat->lda + indexm[i]]; 1015 } 1016 } 1017 PetscFunctionReturn(0); 1018 } 1019 1020 /* -----------------------------------------------------------------*/ 1021 1022 static PetscErrorCode MatLoad_SeqDense(Mat newmat,PetscViewer viewer) 1023 { 1024 Mat_SeqDense *a; 1025 PetscErrorCode ierr; 1026 PetscInt *scols,i,j,nz,header[4]; 1027 int fd; 1028 PetscMPIInt size; 1029 PetscInt *rowlengths = 0,M,N,*cols,grows,gcols; 1030 PetscScalar *vals,*svals,*v,*w; 1031 MPI_Comm comm; 1032 1033 PetscFunctionBegin; 1034 /* force binary viewer to load .info file if it has not yet done so */ 1035 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 1036 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 1037 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1038 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"view must have one processor"); 1039 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1040 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 1041 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Not matrix object"); 1042 M = header[1]; N = header[2]; nz = header[3]; 1043 1044 /* set global size if not set already*/ 1045 if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) { 1046 ierr = MatSetSizes(newmat,M,N,M,N);CHKERRQ(ierr); 1047 } else { 1048 /* if sizes and type are already set, check if the vector global sizes are correct */ 1049 ierr = MatGetSize(newmat,&grows,&gcols);CHKERRQ(ierr); 1050 if (M != grows || N != gcols) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Matrix in file of different length (%d, %d) than the input matrix (%d, %d)",M,N,grows,gcols); 1051 } 1052 a = (Mat_SeqDense*)newmat->data; 1053 if (!a->user_alloc) { 1054 ierr = MatSeqDenseSetPreallocation(newmat,NULL);CHKERRQ(ierr); 1055 } 1056 1057 if (nz == MATRIX_BINARY_FORMAT_DENSE) { /* matrix in file is dense */ 1058 a = (Mat_SeqDense*)newmat->data; 1059 v = a->v; 1060 /* Allocate some temp space to read in the values and then flip them 1061 from row major to column major */ 1062 ierr = PetscMalloc1(M*N > 0 ? M*N : 1,&w);CHKERRQ(ierr); 1063 /* read in nonzero values */ 1064 ierr = PetscBinaryRead(fd,w,M*N,PETSC_SCALAR);CHKERRQ(ierr); 1065 /* now flip the values and store them in the matrix*/ 1066 for (j=0; j<N; j++) { 1067 for (i=0; i<M; i++) { 1068 *v++ =w[i*N+j]; 1069 } 1070 } 1071 ierr = PetscFree(w);CHKERRQ(ierr); 1072 } else { 1073 /* read row lengths */ 1074 ierr = PetscMalloc1(M+1,&rowlengths);CHKERRQ(ierr); 1075 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 1076 1077 a = (Mat_SeqDense*)newmat->data; 1078 v = a->v; 1079 1080 /* read column indices and nonzeros */ 1081 ierr = PetscMalloc1(nz+1,&scols);CHKERRQ(ierr); 1082 cols = scols; 1083 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 1084 ierr = PetscMalloc1(nz+1,&svals);CHKERRQ(ierr); 1085 vals = svals; 1086 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 1087 1088 /* insert into matrix */ 1089 for (i=0; i<M; i++) { 1090 for (j=0; j<rowlengths[i]; j++) v[i+M*scols[j]] = svals[j]; 1091 svals += rowlengths[i]; scols += rowlengths[i]; 1092 } 1093 ierr = PetscFree(vals);CHKERRQ(ierr); 1094 ierr = PetscFree(cols);CHKERRQ(ierr); 1095 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 1096 } 1097 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1098 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1099 PetscFunctionReturn(0); 1100 } 1101 1102 static PetscErrorCode MatView_SeqDense_ASCII(Mat A,PetscViewer viewer) 1103 { 1104 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1105 PetscErrorCode ierr; 1106 PetscInt i,j; 1107 const char *name; 1108 PetscScalar *v; 1109 PetscViewerFormat format; 1110 #if defined(PETSC_USE_COMPLEX) 1111 PetscBool allreal = PETSC_TRUE; 1112 #endif 1113 1114 PetscFunctionBegin; 1115 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1116 if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 1117 PetscFunctionReturn(0); /* do nothing for now */ 1118 } else if (format == PETSC_VIEWER_ASCII_COMMON) { 1119 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 1120 for (i=0; i<A->rmap->n; i++) { 1121 v = a->v + i; 1122 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 1123 for (j=0; j<A->cmap->n; j++) { 1124 #if defined(PETSC_USE_COMPLEX) 1125 if (PetscRealPart(*v) != 0.0 && PetscImaginaryPart(*v) != 0.0) { 1126 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i) ",j,(double)PetscRealPart(*v),(double)PetscImaginaryPart(*v));CHKERRQ(ierr); 1127 } else if (PetscRealPart(*v)) { 1128 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",j,(double)PetscRealPart(*v));CHKERRQ(ierr); 1129 } 1130 #else 1131 if (*v) { 1132 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",j,(double)*v);CHKERRQ(ierr); 1133 } 1134 #endif 1135 v += a->lda; 1136 } 1137 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 1138 } 1139 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 1140 } else { 1141 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 1142 #if defined(PETSC_USE_COMPLEX) 1143 /* determine if matrix has all real values */ 1144 v = a->v; 1145 for (i=0; i<A->rmap->n*A->cmap->n; i++) { 1146 if (PetscImaginaryPart(v[i])) { allreal = PETSC_FALSE; break;} 1147 } 1148 #endif 1149 if (format == PETSC_VIEWER_ASCII_MATLAB) { 1150 ierr = PetscObjectGetName((PetscObject)A,&name);CHKERRQ(ierr); 1151 ierr = PetscViewerASCIIPrintf(viewer,"%% Size = %D %D \n",A->rmap->n,A->cmap->n);CHKERRQ(ierr); 1152 ierr = PetscViewerASCIIPrintf(viewer,"%s = zeros(%D,%D);\n",name,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 1153 ierr = PetscViewerASCIIPrintf(viewer,"%s = [\n",name);CHKERRQ(ierr); 1154 } 1155 1156 for (i=0; i<A->rmap->n; i++) { 1157 v = a->v + i; 1158 for (j=0; j<A->cmap->n; j++) { 1159 #if defined(PETSC_USE_COMPLEX) 1160 if (allreal) { 1161 ierr = PetscViewerASCIIPrintf(viewer,"%18.16e ",(double)PetscRealPart(*v));CHKERRQ(ierr); 1162 } else { 1163 ierr = PetscViewerASCIIPrintf(viewer,"%18.16e + %18.16ei ",(double)PetscRealPart(*v),(double)PetscImaginaryPart(*v));CHKERRQ(ierr); 1164 } 1165 #else 1166 ierr = PetscViewerASCIIPrintf(viewer,"%18.16e ",(double)*v);CHKERRQ(ierr); 1167 #endif 1168 v += a->lda; 1169 } 1170 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 1171 } 1172 if (format == PETSC_VIEWER_ASCII_MATLAB) { 1173 ierr = PetscViewerASCIIPrintf(viewer,"];\n");CHKERRQ(ierr); 1174 } 1175 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 1176 } 1177 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 1178 PetscFunctionReturn(0); 1179 } 1180 1181 static PetscErrorCode MatView_SeqDense_Binary(Mat A,PetscViewer viewer) 1182 { 1183 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1184 PetscErrorCode ierr; 1185 int fd; 1186 PetscInt ict,j,n = A->cmap->n,m = A->rmap->n,i,*col_lens,nz = m*n; 1187 PetscScalar *v,*anonz,*vals; 1188 PetscViewerFormat format; 1189 1190 PetscFunctionBegin; 1191 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1192 1193 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1194 if (format == PETSC_VIEWER_NATIVE) { 1195 /* store the matrix as a dense matrix */ 1196 ierr = PetscMalloc1(4,&col_lens);CHKERRQ(ierr); 1197 1198 col_lens[0] = MAT_FILE_CLASSID; 1199 col_lens[1] = m; 1200 col_lens[2] = n; 1201 col_lens[3] = MATRIX_BINARY_FORMAT_DENSE; 1202 1203 ierr = PetscBinaryWrite(fd,col_lens,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1204 ierr = PetscFree(col_lens);CHKERRQ(ierr); 1205 1206 /* write out matrix, by rows */ 1207 ierr = PetscMalloc1(m*n+1,&vals);CHKERRQ(ierr); 1208 v = a->v; 1209 for (j=0; j<n; j++) { 1210 for (i=0; i<m; i++) { 1211 vals[j + i*n] = *v++; 1212 } 1213 } 1214 ierr = PetscBinaryWrite(fd,vals,n*m,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 1215 ierr = PetscFree(vals);CHKERRQ(ierr); 1216 } else { 1217 ierr = PetscMalloc1(4+nz,&col_lens);CHKERRQ(ierr); 1218 1219 col_lens[0] = MAT_FILE_CLASSID; 1220 col_lens[1] = m; 1221 col_lens[2] = n; 1222 col_lens[3] = nz; 1223 1224 /* store lengths of each row and write (including header) to file */ 1225 for (i=0; i<m; i++) col_lens[4+i] = n; 1226 ierr = PetscBinaryWrite(fd,col_lens,4+m,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1227 1228 /* Possibly should write in smaller increments, not whole matrix at once? */ 1229 /* store column indices (zero start index) */ 1230 ict = 0; 1231 for (i=0; i<m; i++) { 1232 for (j=0; j<n; j++) col_lens[ict++] = j; 1233 } 1234 ierr = PetscBinaryWrite(fd,col_lens,nz,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 1235 ierr = PetscFree(col_lens);CHKERRQ(ierr); 1236 1237 /* store nonzero values */ 1238 ierr = PetscMalloc1(nz+1,&anonz);CHKERRQ(ierr); 1239 ict = 0; 1240 for (i=0; i<m; i++) { 1241 v = a->v + i; 1242 for (j=0; j<n; j++) { 1243 anonz[ict++] = *v; v += a->lda; 1244 } 1245 } 1246 ierr = PetscBinaryWrite(fd,anonz,nz,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 1247 ierr = PetscFree(anonz);CHKERRQ(ierr); 1248 } 1249 PetscFunctionReturn(0); 1250 } 1251 1252 #include <petscdraw.h> 1253 static PetscErrorCode MatView_SeqDense_Draw_Zoom(PetscDraw draw,void *Aa) 1254 { 1255 Mat A = (Mat) Aa; 1256 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1257 PetscErrorCode ierr; 1258 PetscInt m = A->rmap->n,n = A->cmap->n,i,j; 1259 int color = PETSC_DRAW_WHITE; 1260 PetscScalar *v = a->v; 1261 PetscViewer viewer; 1262 PetscReal xl,yl,xr,yr,x_l,x_r,y_l,y_r; 1263 PetscViewerFormat format; 1264 1265 PetscFunctionBegin; 1266 ierr = PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);CHKERRQ(ierr); 1267 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1268 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 1269 1270 /* Loop over matrix elements drawing boxes */ 1271 1272 if (format != PETSC_VIEWER_DRAW_CONTOUR) { 1273 ierr = PetscDrawCollectiveBegin(draw);CHKERRQ(ierr); 1274 /* Blue for negative and Red for positive */ 1275 for (j = 0; j < n; j++) { 1276 x_l = j; x_r = x_l + 1.0; 1277 for (i = 0; i < m; i++) { 1278 y_l = m - i - 1.0; 1279 y_r = y_l + 1.0; 1280 if (PetscRealPart(v[j*m+i]) > 0.) { 1281 color = PETSC_DRAW_RED; 1282 } else if (PetscRealPart(v[j*m+i]) < 0.) { 1283 color = PETSC_DRAW_BLUE; 1284 } else { 1285 continue; 1286 } 1287 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 1288 } 1289 } 1290 ierr = PetscDrawCollectiveEnd(draw);CHKERRQ(ierr); 1291 } else { 1292 /* use contour shading to indicate magnitude of values */ 1293 /* first determine max of all nonzero values */ 1294 PetscReal minv = 0.0, maxv = 0.0; 1295 PetscDraw popup; 1296 1297 for (i=0; i < m*n; i++) { 1298 if (PetscAbsScalar(v[i]) > maxv) maxv = PetscAbsScalar(v[i]); 1299 } 1300 if (minv >= maxv) maxv = minv + PETSC_SMALL; 1301 ierr = PetscDrawGetPopup(draw,&popup);CHKERRQ(ierr); 1302 ierr = PetscDrawScalePopup(popup,minv,maxv);CHKERRQ(ierr); 1303 1304 ierr = PetscDrawCollectiveBegin(draw);CHKERRQ(ierr); 1305 for (j=0; j<n; j++) { 1306 x_l = j; 1307 x_r = x_l + 1.0; 1308 for (i=0; i<m; i++) { 1309 y_l = m - i - 1.0; 1310 y_r = y_l + 1.0; 1311 color = PetscDrawRealToColor(PetscAbsScalar(v[j*m+i]),minv,maxv); 1312 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 1313 } 1314 } 1315 ierr = PetscDrawCollectiveEnd(draw);CHKERRQ(ierr); 1316 } 1317 PetscFunctionReturn(0); 1318 } 1319 1320 static PetscErrorCode MatView_SeqDense_Draw(Mat A,PetscViewer viewer) 1321 { 1322 PetscDraw draw; 1323 PetscBool isnull; 1324 PetscReal xr,yr,xl,yl,h,w; 1325 PetscErrorCode ierr; 1326 1327 PetscFunctionBegin; 1328 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1329 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); 1330 if (isnull) PetscFunctionReturn(0); 1331 1332 xr = A->cmap->n; yr = A->rmap->n; h = yr/10.0; w = xr/10.0; 1333 xr += w; yr += h; xl = -w; yl = -h; 1334 ierr = PetscDrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); 1335 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr); 1336 ierr = PetscDrawZoom(draw,MatView_SeqDense_Draw_Zoom,A);CHKERRQ(ierr); 1337 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",NULL);CHKERRQ(ierr); 1338 ierr = PetscDrawSave(draw);CHKERRQ(ierr); 1339 PetscFunctionReturn(0); 1340 } 1341 1342 PetscErrorCode MatView_SeqDense(Mat A,PetscViewer viewer) 1343 { 1344 PetscErrorCode ierr; 1345 PetscBool iascii,isbinary,isdraw; 1346 1347 PetscFunctionBegin; 1348 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1349 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1350 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1351 1352 if (iascii) { 1353 ierr = MatView_SeqDense_ASCII(A,viewer);CHKERRQ(ierr); 1354 } else if (isbinary) { 1355 ierr = MatView_SeqDense_Binary(A,viewer);CHKERRQ(ierr); 1356 } else if (isdraw) { 1357 ierr = MatView_SeqDense_Draw(A,viewer);CHKERRQ(ierr); 1358 } 1359 PetscFunctionReturn(0); 1360 } 1361 1362 static PetscErrorCode MatDensePlaceArray_SeqDense(Mat A,const PetscScalar array[]) 1363 { 1364 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1365 1366 PetscFunctionBegin; 1367 a->unplacedarray = a->v; 1368 a->unplaced_user_alloc = a->user_alloc; 1369 a->v = (PetscScalar*) array; 1370 PetscFunctionReturn(0); 1371 } 1372 1373 static PetscErrorCode MatDenseResetArray_SeqDense(Mat A) 1374 { 1375 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1376 1377 PetscFunctionBegin; 1378 a->v = a->unplacedarray; 1379 a->user_alloc = a->unplaced_user_alloc; 1380 a->unplacedarray = NULL; 1381 PetscFunctionReturn(0); 1382 } 1383 1384 static PetscErrorCode MatDestroy_SeqDense(Mat mat) 1385 { 1386 Mat_SeqDense *l = (Mat_SeqDense*)mat->data; 1387 PetscErrorCode ierr; 1388 1389 PetscFunctionBegin; 1390 #if defined(PETSC_USE_LOG) 1391 PetscLogObjectState((PetscObject)mat,"Rows %D Cols %D",mat->rmap->n,mat->cmap->n); 1392 #endif 1393 ierr = PetscFree(l->pivots);CHKERRQ(ierr); 1394 ierr = PetscFree(l->fwork);CHKERRQ(ierr); 1395 ierr = MatDestroy(&l->ptapwork);CHKERRQ(ierr); 1396 if (!l->user_alloc) {ierr = PetscFree(l->v);CHKERRQ(ierr);} 1397 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1398 1399 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1400 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseGetArray_C",NULL);CHKERRQ(ierr); 1401 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDensePlaceArray_C",NULL);CHKERRQ(ierr); 1402 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseResetArray_C",NULL);CHKERRQ(ierr); 1403 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDenseRestoreArray_C",NULL);CHKERRQ(ierr); 1404 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_seqdense_seqaij_C",NULL);CHKERRQ(ierr); 1405 #if defined(PETSC_HAVE_ELEMENTAL) 1406 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_seqdense_elemental_C",NULL);CHKERRQ(ierr); 1407 #endif 1408 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatSeqDenseSetPreallocation_C",NULL);CHKERRQ(ierr); 1409 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMult_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1410 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMultSymbolic_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1411 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMatMultNumeric_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1412 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatPtAP_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1413 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMult_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1414 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMultSymbolic_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1415 ierr = PetscObjectComposeFunction((PetscObject)mat,"MatTransposeMatMultNumeric_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1416 PetscFunctionReturn(0); 1417 } 1418 1419 static PetscErrorCode MatTranspose_SeqDense(Mat A,MatReuse reuse,Mat *matout) 1420 { 1421 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1422 PetscErrorCode ierr; 1423 PetscInt k,j,m,n,M; 1424 PetscScalar *v,tmp; 1425 1426 PetscFunctionBegin; 1427 v = mat->v; m = A->rmap->n; M = mat->lda; n = A->cmap->n; 1428 if (reuse == MAT_INPLACE_MATRIX) { /* in place transpose */ 1429 if (m != n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can not transpose non-square matrix in place"); 1430 else { 1431 for (j=0; j<m; j++) { 1432 for (k=0; k<j; k++) { 1433 tmp = v[j + k*M]; 1434 v[j + k*M] = v[k + j*M]; 1435 v[k + j*M] = tmp; 1436 } 1437 } 1438 } 1439 } else { /* out-of-place transpose */ 1440 Mat tmat; 1441 Mat_SeqDense *tmatd; 1442 PetscScalar *v2; 1443 PetscInt M2; 1444 1445 if (reuse == MAT_INITIAL_MATRIX) { 1446 ierr = MatCreate(PetscObjectComm((PetscObject)A),&tmat);CHKERRQ(ierr); 1447 ierr = MatSetSizes(tmat,A->cmap->n,A->rmap->n,A->cmap->n,A->rmap->n);CHKERRQ(ierr); 1448 ierr = MatSetType(tmat,((PetscObject)A)->type_name);CHKERRQ(ierr); 1449 ierr = MatSeqDenseSetPreallocation(tmat,NULL);CHKERRQ(ierr); 1450 } else { 1451 tmat = *matout; 1452 } 1453 tmatd = (Mat_SeqDense*)tmat->data; 1454 v = mat->v; v2 = tmatd->v; M2 = tmatd->lda; 1455 for (j=0; j<n; j++) { 1456 for (k=0; k<m; k++) v2[j + k*M2] = v[k + j*M]; 1457 } 1458 ierr = MatAssemblyBegin(tmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1459 ierr = MatAssemblyEnd(tmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1460 *matout = tmat; 1461 } 1462 PetscFunctionReturn(0); 1463 } 1464 1465 static PetscErrorCode MatEqual_SeqDense(Mat A1,Mat A2,PetscBool *flg) 1466 { 1467 Mat_SeqDense *mat1 = (Mat_SeqDense*)A1->data; 1468 Mat_SeqDense *mat2 = (Mat_SeqDense*)A2->data; 1469 PetscInt i,j; 1470 PetscScalar *v1,*v2; 1471 1472 PetscFunctionBegin; 1473 if (A1->rmap->n != A2->rmap->n) {*flg = PETSC_FALSE; PetscFunctionReturn(0);} 1474 if (A1->cmap->n != A2->cmap->n) {*flg = PETSC_FALSE; PetscFunctionReturn(0);} 1475 for (i=0; i<A1->rmap->n; i++) { 1476 v1 = mat1->v+i; v2 = mat2->v+i; 1477 for (j=0; j<A1->cmap->n; j++) { 1478 if (*v1 != *v2) {*flg = PETSC_FALSE; PetscFunctionReturn(0);} 1479 v1 += mat1->lda; v2 += mat2->lda; 1480 } 1481 } 1482 *flg = PETSC_TRUE; 1483 PetscFunctionReturn(0); 1484 } 1485 1486 static PetscErrorCode MatGetDiagonal_SeqDense(Mat A,Vec v) 1487 { 1488 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1489 PetscErrorCode ierr; 1490 PetscInt i,n,len; 1491 PetscScalar *x,zero = 0.0; 1492 1493 PetscFunctionBegin; 1494 ierr = VecSet(v,zero);CHKERRQ(ierr); 1495 ierr = VecGetSize(v,&n);CHKERRQ(ierr); 1496 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1497 len = PetscMin(A->rmap->n,A->cmap->n); 1498 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming mat and vec"); 1499 for (i=0; i<len; i++) { 1500 x[i] = mat->v[i*mat->lda + i]; 1501 } 1502 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1503 PetscFunctionReturn(0); 1504 } 1505 1506 static PetscErrorCode MatDiagonalScale_SeqDense(Mat A,Vec ll,Vec rr) 1507 { 1508 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1509 const PetscScalar *l,*r; 1510 PetscScalar x,*v; 1511 PetscErrorCode ierr; 1512 PetscInt i,j,m = A->rmap->n,n = A->cmap->n; 1513 1514 PetscFunctionBegin; 1515 if (ll) { 1516 ierr = VecGetSize(ll,&m);CHKERRQ(ierr); 1517 ierr = VecGetArrayRead(ll,&l);CHKERRQ(ierr); 1518 if (m != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left scaling vec wrong size"); 1519 for (i=0; i<m; i++) { 1520 x = l[i]; 1521 v = mat->v + i; 1522 for (j=0; j<n; j++) { (*v) *= x; v+= mat->lda;} 1523 } 1524 ierr = VecRestoreArrayRead(ll,&l);CHKERRQ(ierr); 1525 ierr = PetscLogFlops(1.0*n*m);CHKERRQ(ierr); 1526 } 1527 if (rr) { 1528 ierr = VecGetSize(rr,&n);CHKERRQ(ierr); 1529 ierr = VecGetArrayRead(rr,&r);CHKERRQ(ierr); 1530 if (n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Right scaling vec wrong size"); 1531 for (i=0; i<n; i++) { 1532 x = r[i]; 1533 v = mat->v + i*mat->lda; 1534 for (j=0; j<m; j++) (*v++) *= x; 1535 } 1536 ierr = VecRestoreArrayRead(rr,&r);CHKERRQ(ierr); 1537 ierr = PetscLogFlops(1.0*n*m);CHKERRQ(ierr); 1538 } 1539 PetscFunctionReturn(0); 1540 } 1541 1542 static PetscErrorCode MatNorm_SeqDense(Mat A,NormType type,PetscReal *nrm) 1543 { 1544 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1545 PetscScalar *v = mat->v; 1546 PetscReal sum = 0.0; 1547 PetscInt lda =mat->lda,m=A->rmap->n,i,j; 1548 PetscErrorCode ierr; 1549 1550 PetscFunctionBegin; 1551 if (type == NORM_FROBENIUS) { 1552 if (lda>m) { 1553 for (j=0; j<A->cmap->n; j++) { 1554 v = mat->v+j*lda; 1555 for (i=0; i<m; i++) { 1556 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1557 } 1558 } 1559 } else { 1560 #if defined(PETSC_USE_REAL___FP16) 1561 PetscBLASInt one = 1,cnt = A->cmap->n*A->rmap->n; 1562 *nrm = BLASnrm2_(&cnt,v,&one); 1563 } 1564 #else 1565 for (i=0; i<A->cmap->n*A->rmap->n; i++) { 1566 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1567 } 1568 } 1569 *nrm = PetscSqrtReal(sum); 1570 #endif 1571 ierr = PetscLogFlops(2.0*A->cmap->n*A->rmap->n);CHKERRQ(ierr); 1572 } else if (type == NORM_1) { 1573 *nrm = 0.0; 1574 for (j=0; j<A->cmap->n; j++) { 1575 v = mat->v + j*mat->lda; 1576 sum = 0.0; 1577 for (i=0; i<A->rmap->n; i++) { 1578 sum += PetscAbsScalar(*v); v++; 1579 } 1580 if (sum > *nrm) *nrm = sum; 1581 } 1582 ierr = PetscLogFlops(1.0*A->cmap->n*A->rmap->n);CHKERRQ(ierr); 1583 } else if (type == NORM_INFINITY) { 1584 *nrm = 0.0; 1585 for (j=0; j<A->rmap->n; j++) { 1586 v = mat->v + j; 1587 sum = 0.0; 1588 for (i=0; i<A->cmap->n; i++) { 1589 sum += PetscAbsScalar(*v); v += mat->lda; 1590 } 1591 if (sum > *nrm) *nrm = sum; 1592 } 1593 ierr = PetscLogFlops(1.0*A->cmap->n*A->rmap->n);CHKERRQ(ierr); 1594 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No two norm"); 1595 PetscFunctionReturn(0); 1596 } 1597 1598 static PetscErrorCode MatSetOption_SeqDense(Mat A,MatOption op,PetscBool flg) 1599 { 1600 Mat_SeqDense *aij = (Mat_SeqDense*)A->data; 1601 PetscErrorCode ierr; 1602 1603 PetscFunctionBegin; 1604 switch (op) { 1605 case MAT_ROW_ORIENTED: 1606 aij->roworiented = flg; 1607 break; 1608 case MAT_NEW_NONZERO_LOCATIONS: 1609 case MAT_NEW_NONZERO_LOCATION_ERR: 1610 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1611 case MAT_NEW_DIAGONALS: 1612 case MAT_KEEP_NONZERO_PATTERN: 1613 case MAT_IGNORE_OFF_PROC_ENTRIES: 1614 case MAT_USE_HASH_TABLE: 1615 case MAT_IGNORE_ZERO_ENTRIES: 1616 case MAT_IGNORE_LOWER_TRIANGULAR: 1617 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1618 break; 1619 case MAT_SPD: 1620 case MAT_SYMMETRIC: 1621 case MAT_STRUCTURALLY_SYMMETRIC: 1622 case MAT_HERMITIAN: 1623 case MAT_SYMMETRY_ETERNAL: 1624 /* These options are handled directly by MatSetOption() */ 1625 break; 1626 default: 1627 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %s",MatOptions[op]); 1628 } 1629 PetscFunctionReturn(0); 1630 } 1631 1632 static PetscErrorCode MatZeroEntries_SeqDense(Mat A) 1633 { 1634 Mat_SeqDense *l = (Mat_SeqDense*)A->data; 1635 PetscErrorCode ierr; 1636 PetscInt lda=l->lda,m=A->rmap->n,j; 1637 1638 PetscFunctionBegin; 1639 if (lda>m) { 1640 for (j=0; j<A->cmap->n; j++) { 1641 ierr = PetscMemzero(l->v+j*lda,m*sizeof(PetscScalar));CHKERRQ(ierr); 1642 } 1643 } else { 1644 ierr = PetscMemzero(l->v,A->rmap->n*A->cmap->n*sizeof(PetscScalar));CHKERRQ(ierr); 1645 } 1646 PetscFunctionReturn(0); 1647 } 1648 1649 static PetscErrorCode MatZeroRows_SeqDense(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1650 { 1651 PetscErrorCode ierr; 1652 Mat_SeqDense *l = (Mat_SeqDense*)A->data; 1653 PetscInt m = l->lda, n = A->cmap->n, i,j; 1654 PetscScalar *slot,*bb; 1655 const PetscScalar *xx; 1656 1657 PetscFunctionBegin; 1658 #if defined(PETSC_USE_DEBUG) 1659 for (i=0; i<N; i++) { 1660 if (rows[i] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row requested to be zeroed"); 1661 if (rows[i] >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D requested to be zeroed greater than or equal number of rows %D",rows[i],A->rmap->n); 1662 } 1663 #endif 1664 1665 /* fix right hand side if needed */ 1666 if (x && b) { 1667 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1668 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1669 for (i=0; i<N; i++) bb[rows[i]] = diag*xx[rows[i]]; 1670 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1671 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1672 } 1673 1674 for (i=0; i<N; i++) { 1675 slot = l->v + rows[i]; 1676 for (j=0; j<n; j++) { *slot = 0.0; slot += m;} 1677 } 1678 if (diag != 0.0) { 1679 if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only coded for square matrices"); 1680 for (i=0; i<N; i++) { 1681 slot = l->v + (m+1)*rows[i]; 1682 *slot = diag; 1683 } 1684 } 1685 PetscFunctionReturn(0); 1686 } 1687 1688 static PetscErrorCode MatDenseGetArray_SeqDense(Mat A,PetscScalar *array[]) 1689 { 1690 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1691 1692 PetscFunctionBegin; 1693 if (mat->lda != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Cannot get array for Dense matrices with LDA different from number of rows"); 1694 *array = mat->v; 1695 PetscFunctionReturn(0); 1696 } 1697 1698 static PetscErrorCode MatDenseRestoreArray_SeqDense(Mat A,PetscScalar *array[]) 1699 { 1700 PetscFunctionBegin; 1701 *array = 0; /* user cannot accidently use the array later */ 1702 PetscFunctionReturn(0); 1703 } 1704 1705 /*@C 1706 MatDenseGetArray - gives access to the array where the data for a SeqDense matrix is stored 1707 1708 Not Collective 1709 1710 Input Parameter: 1711 . mat - a MATSEQDENSE or MATMPIDENSE matrix 1712 1713 Output Parameter: 1714 . array - pointer to the data 1715 1716 Level: intermediate 1717 1718 .seealso: MatDenseRestoreArray() 1719 @*/ 1720 PetscErrorCode MatDenseGetArray(Mat A,PetscScalar **array) 1721 { 1722 PetscErrorCode ierr; 1723 1724 PetscFunctionBegin; 1725 ierr = PetscUseMethod(A,"MatDenseGetArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 1726 PetscFunctionReturn(0); 1727 } 1728 1729 /*@C 1730 MatDenseRestoreArray - returns access to the array where the data for a dense matrix is stored obtained by MatDenseGetArray() 1731 1732 Not Collective 1733 1734 Input Parameters: 1735 . mat - a MATSEQDENSE or MATMPIDENSE matrix 1736 . array - pointer to the data 1737 1738 Level: intermediate 1739 1740 .seealso: MatDenseGetArray() 1741 @*/ 1742 PetscErrorCode MatDenseRestoreArray(Mat A,PetscScalar **array) 1743 { 1744 PetscErrorCode ierr; 1745 1746 PetscFunctionBegin; 1747 ierr = PetscUseMethod(A,"MatDenseRestoreArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 1748 PetscFunctionReturn(0); 1749 } 1750 1751 static PetscErrorCode MatCreateSubMatrix_SeqDense(Mat A,IS isrow,IS iscol,PetscInt cs,MatReuse scall,Mat *B) 1752 { 1753 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1754 PetscErrorCode ierr; 1755 PetscInt i,j,nrows,ncols; 1756 const PetscInt *irow,*icol; 1757 PetscScalar *av,*bv,*v = mat->v; 1758 Mat newmat; 1759 1760 PetscFunctionBegin; 1761 ierr = ISGetIndices(isrow,&irow);CHKERRQ(ierr); 1762 ierr = ISGetIndices(iscol,&icol);CHKERRQ(ierr); 1763 ierr = ISGetLocalSize(isrow,&nrows);CHKERRQ(ierr); 1764 ierr = ISGetLocalSize(iscol,&ncols);CHKERRQ(ierr); 1765 1766 /* Check submatrixcall */ 1767 if (scall == MAT_REUSE_MATRIX) { 1768 PetscInt n_cols,n_rows; 1769 ierr = MatGetSize(*B,&n_rows,&n_cols);CHKERRQ(ierr); 1770 if (n_rows != nrows || n_cols != ncols) { 1771 /* resize the result matrix to match number of requested rows/columns */ 1772 ierr = MatSetSizes(*B,nrows,ncols,nrows,ncols);CHKERRQ(ierr); 1773 } 1774 newmat = *B; 1775 } else { 1776 /* Create and fill new matrix */ 1777 ierr = MatCreate(PetscObjectComm((PetscObject)A),&newmat);CHKERRQ(ierr); 1778 ierr = MatSetSizes(newmat,nrows,ncols,nrows,ncols);CHKERRQ(ierr); 1779 ierr = MatSetType(newmat,((PetscObject)A)->type_name);CHKERRQ(ierr); 1780 ierr = MatSeqDenseSetPreallocation(newmat,NULL);CHKERRQ(ierr); 1781 } 1782 1783 /* Now extract the data pointers and do the copy,column at a time */ 1784 bv = ((Mat_SeqDense*)newmat->data)->v; 1785 1786 for (i=0; i<ncols; i++) { 1787 av = v + mat->lda*icol[i]; 1788 for (j=0; j<nrows; j++) *bv++ = av[irow[j]]; 1789 } 1790 1791 /* Assemble the matrices so that the correct flags are set */ 1792 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1793 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1794 1795 /* Free work space */ 1796 ierr = ISRestoreIndices(isrow,&irow);CHKERRQ(ierr); 1797 ierr = ISRestoreIndices(iscol,&icol);CHKERRQ(ierr); 1798 *B = newmat; 1799 PetscFunctionReturn(0); 1800 } 1801 1802 static PetscErrorCode MatCreateSubMatrices_SeqDense(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 1803 { 1804 PetscErrorCode ierr; 1805 PetscInt i; 1806 1807 PetscFunctionBegin; 1808 if (scall == MAT_INITIAL_MATRIX) { 1809 ierr = PetscCalloc1(n+1,B);CHKERRQ(ierr); 1810 } 1811 1812 for (i=0; i<n; i++) { 1813 ierr = MatCreateSubMatrix_SeqDense(A,irow[i],icol[i],PETSC_DECIDE,scall,&(*B)[i]);CHKERRQ(ierr); 1814 } 1815 PetscFunctionReturn(0); 1816 } 1817 1818 static PetscErrorCode MatAssemblyBegin_SeqDense(Mat mat,MatAssemblyType mode) 1819 { 1820 PetscFunctionBegin; 1821 PetscFunctionReturn(0); 1822 } 1823 1824 static PetscErrorCode MatAssemblyEnd_SeqDense(Mat mat,MatAssemblyType mode) 1825 { 1826 PetscFunctionBegin; 1827 PetscFunctionReturn(0); 1828 } 1829 1830 static PetscErrorCode MatCopy_SeqDense(Mat A,Mat B,MatStructure str) 1831 { 1832 Mat_SeqDense *a = (Mat_SeqDense*)A->data,*b = (Mat_SeqDense*)B->data; 1833 PetscErrorCode ierr; 1834 PetscInt lda1=a->lda,lda2=b->lda, m=A->rmap->n,n=A->cmap->n, j; 1835 1836 PetscFunctionBegin; 1837 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1838 if (A->ops->copy != B->ops->copy) { 1839 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1840 PetscFunctionReturn(0); 1841 } 1842 if (m != B->rmap->n || n != B->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"size(B) != size(A)"); 1843 if (lda1>m || lda2>m) { 1844 for (j=0; j<n; j++) { 1845 ierr = PetscMemcpy(b->v+j*lda2,a->v+j*lda1,m*sizeof(PetscScalar));CHKERRQ(ierr); 1846 } 1847 } else { 1848 ierr = PetscMemcpy(b->v,a->v,A->rmap->n*A->cmap->n*sizeof(PetscScalar));CHKERRQ(ierr); 1849 } 1850 ierr = PetscObjectStateIncrease((PetscObject)B);CHKERRQ(ierr); 1851 PetscFunctionReturn(0); 1852 } 1853 1854 static PetscErrorCode MatSetUp_SeqDense(Mat A) 1855 { 1856 PetscErrorCode ierr; 1857 1858 PetscFunctionBegin; 1859 ierr = MatSeqDenseSetPreallocation(A,0);CHKERRQ(ierr); 1860 PetscFunctionReturn(0); 1861 } 1862 1863 static PetscErrorCode MatConjugate_SeqDense(Mat A) 1864 { 1865 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1866 PetscInt i,nz = A->rmap->n*A->cmap->n; 1867 PetscScalar *aa = a->v; 1868 1869 PetscFunctionBegin; 1870 for (i=0; i<nz; i++) aa[i] = PetscConj(aa[i]); 1871 PetscFunctionReturn(0); 1872 } 1873 1874 static PetscErrorCode MatRealPart_SeqDense(Mat A) 1875 { 1876 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1877 PetscInt i,nz = A->rmap->n*A->cmap->n; 1878 PetscScalar *aa = a->v; 1879 1880 PetscFunctionBegin; 1881 for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]); 1882 PetscFunctionReturn(0); 1883 } 1884 1885 static PetscErrorCode MatImaginaryPart_SeqDense(Mat A) 1886 { 1887 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1888 PetscInt i,nz = A->rmap->n*A->cmap->n; 1889 PetscScalar *aa = a->v; 1890 1891 PetscFunctionBegin; 1892 for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]); 1893 PetscFunctionReturn(0); 1894 } 1895 1896 /* ----------------------------------------------------------------*/ 1897 PETSC_INTERN PetscErrorCode MatMatMult_SeqDense_SeqDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 1898 { 1899 PetscErrorCode ierr; 1900 1901 PetscFunctionBegin; 1902 if (scall == MAT_INITIAL_MATRIX) { 1903 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 1904 ierr = MatMatMultSymbolic_SeqDense_SeqDense(A,B,fill,C);CHKERRQ(ierr); 1905 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 1906 } 1907 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 1908 ierr = MatMatMultNumeric_SeqDense_SeqDense(A,B,*C);CHKERRQ(ierr); 1909 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 1910 PetscFunctionReturn(0); 1911 } 1912 1913 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqDense(Mat A,Mat B,PetscReal fill,Mat *C) 1914 { 1915 PetscErrorCode ierr; 1916 PetscInt m=A->rmap->n,n=B->cmap->n; 1917 Mat Cmat; 1918 1919 PetscFunctionBegin; 1920 if (A->cmap->n != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"A->cmap->n %d != B->rmap->n %d\n",A->cmap->n,B->rmap->n); 1921 ierr = MatCreate(PETSC_COMM_SELF,&Cmat);CHKERRQ(ierr); 1922 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 1923 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 1924 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 1925 1926 *C = Cmat; 1927 PetscFunctionReturn(0); 1928 } 1929 1930 PetscErrorCode MatMatMultNumeric_SeqDense_SeqDense(Mat A,Mat B,Mat C) 1931 { 1932 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1933 Mat_SeqDense *b = (Mat_SeqDense*)B->data; 1934 Mat_SeqDense *c = (Mat_SeqDense*)C->data; 1935 PetscBLASInt m,n,k; 1936 PetscScalar _DOne=1.0,_DZero=0.0; 1937 PetscErrorCode ierr; 1938 PetscBool flg; 1939 1940 PetscFunctionBegin; 1941 ierr = PetscObjectTypeCompare((PetscObject)B,MATSEQDENSE,&flg);CHKERRQ(ierr); 1942 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Second matrix must be dense"); 1943 1944 /* Handle case where where user provided the final C matrix rather than calling MatMatMult() with MAT_INITIAL_MATRIX*/ 1945 ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQAIJ,&flg);CHKERRQ(ierr); 1946 if (flg) { 1947 C->ops->matmultnumeric = MatMatMultNumeric_SeqAIJ_SeqDense; 1948 ierr = (*C->ops->matmultnumeric)(A,B,C);CHKERRQ(ierr); 1949 PetscFunctionReturn(0); 1950 } 1951 1952 ierr = PetscObjectTypeCompare((PetscObject)A,MATSEQDENSE,&flg);CHKERRQ(ierr); 1953 if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"First matrix must be dense"); 1954 ierr = PetscBLASIntCast(C->rmap->n,&m);CHKERRQ(ierr); 1955 ierr = PetscBLASIntCast(C->cmap->n,&n);CHKERRQ(ierr); 1956 ierr = PetscBLASIntCast(A->cmap->n,&k);CHKERRQ(ierr); 1957 PetscStackCallBLAS("BLASgemm",BLASgemm_("N","N",&m,&n,&k,&_DOne,a->v,&a->lda,b->v,&b->lda,&_DZero,c->v,&c->lda)); 1958 PetscFunctionReturn(0); 1959 } 1960 1961 PetscErrorCode MatMatTransposeMult_SeqDense_SeqDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 1962 { 1963 PetscErrorCode ierr; 1964 1965 PetscFunctionBegin; 1966 if (scall == MAT_INITIAL_MATRIX) { 1967 ierr = PetscLogEventBegin(MAT_MatTransposeMultSymbolic,A,B,0,0);CHKERRQ(ierr); 1968 ierr = MatMatTransposeMultSymbolic_SeqDense_SeqDense(A,B,fill,C);CHKERRQ(ierr); 1969 ierr = PetscLogEventEnd(MAT_MatTransposeMultSymbolic,A,B,0,0);CHKERRQ(ierr); 1970 } 1971 ierr = PetscLogEventBegin(MAT_MatTransposeMultNumeric,A,B,0,0);CHKERRQ(ierr); 1972 ierr = MatMatTransposeMultNumeric_SeqDense_SeqDense(A,B,*C);CHKERRQ(ierr); 1973 ierr = PetscLogEventEnd(MAT_MatTransposeMultNumeric,A,B,0,0);CHKERRQ(ierr); 1974 PetscFunctionReturn(0); 1975 } 1976 1977 PetscErrorCode MatMatTransposeMultSymbolic_SeqDense_SeqDense(Mat A,Mat B,PetscReal fill,Mat *C) 1978 { 1979 PetscErrorCode ierr; 1980 PetscInt m=A->rmap->n,n=B->rmap->n; 1981 Mat Cmat; 1982 1983 PetscFunctionBegin; 1984 if (A->cmap->n != B->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"A->cmap->n %d != B->cmap->n %d\n",A->cmap->n,B->cmap->n); 1985 ierr = MatCreate(PETSC_COMM_SELF,&Cmat);CHKERRQ(ierr); 1986 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 1987 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 1988 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 1989 1990 Cmat->assembled = PETSC_TRUE; 1991 1992 *C = Cmat; 1993 PetscFunctionReturn(0); 1994 } 1995 1996 PetscErrorCode MatMatTransposeMultNumeric_SeqDense_SeqDense(Mat A,Mat B,Mat C) 1997 { 1998 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1999 Mat_SeqDense *b = (Mat_SeqDense*)B->data; 2000 Mat_SeqDense *c = (Mat_SeqDense*)C->data; 2001 PetscBLASInt m,n,k; 2002 PetscScalar _DOne=1.0,_DZero=0.0; 2003 PetscErrorCode ierr; 2004 2005 PetscFunctionBegin; 2006 ierr = PetscBLASIntCast(A->rmap->n,&m);CHKERRQ(ierr); 2007 ierr = PetscBLASIntCast(B->rmap->n,&n);CHKERRQ(ierr); 2008 ierr = PetscBLASIntCast(A->cmap->n,&k);CHKERRQ(ierr); 2009 PetscStackCallBLAS("BLASgemm",BLASgemm_("N","T",&m,&n,&k,&_DOne,a->v,&a->lda,b->v,&b->lda,&_DZero,c->v,&c->lda)); 2010 PetscFunctionReturn(0); 2011 } 2012 2013 PetscErrorCode MatTransposeMatMult_SeqDense_SeqDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 2014 { 2015 PetscErrorCode ierr; 2016 2017 PetscFunctionBegin; 2018 if (scall == MAT_INITIAL_MATRIX) { 2019 ierr = PetscLogEventBegin(MAT_TransposeMatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 2020 ierr = MatTransposeMatMultSymbolic_SeqDense_SeqDense(A,B,fill,C);CHKERRQ(ierr); 2021 ierr = PetscLogEventEnd(MAT_TransposeMatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 2022 } 2023 ierr = PetscLogEventBegin(MAT_TransposeMatMultNumeric,A,B,0,0);CHKERRQ(ierr); 2024 ierr = MatTransposeMatMultNumeric_SeqDense_SeqDense(A,B,*C);CHKERRQ(ierr); 2025 ierr = PetscLogEventEnd(MAT_TransposeMatMultNumeric,A,B,0,0);CHKERRQ(ierr); 2026 PetscFunctionReturn(0); 2027 } 2028 2029 PetscErrorCode MatTransposeMatMultSymbolic_SeqDense_SeqDense(Mat A,Mat B,PetscReal fill,Mat *C) 2030 { 2031 PetscErrorCode ierr; 2032 PetscInt m=A->cmap->n,n=B->cmap->n; 2033 Mat Cmat; 2034 2035 PetscFunctionBegin; 2036 if (A->rmap->n != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"A->rmap->n %d != B->rmap->n %d\n",A->rmap->n,B->rmap->n); 2037 ierr = MatCreate(PETSC_COMM_SELF,&Cmat);CHKERRQ(ierr); 2038 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 2039 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 2040 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 2041 2042 Cmat->assembled = PETSC_TRUE; 2043 2044 *C = Cmat; 2045 PetscFunctionReturn(0); 2046 } 2047 2048 PetscErrorCode MatTransposeMatMultNumeric_SeqDense_SeqDense(Mat A,Mat B,Mat C) 2049 { 2050 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 2051 Mat_SeqDense *b = (Mat_SeqDense*)B->data; 2052 Mat_SeqDense *c = (Mat_SeqDense*)C->data; 2053 PetscBLASInt m,n,k; 2054 PetscScalar _DOne=1.0,_DZero=0.0; 2055 PetscErrorCode ierr; 2056 2057 PetscFunctionBegin; 2058 ierr = PetscBLASIntCast(C->rmap->n,&m);CHKERRQ(ierr); 2059 ierr = PetscBLASIntCast(C->cmap->n,&n);CHKERRQ(ierr); 2060 ierr = PetscBLASIntCast(A->rmap->n,&k);CHKERRQ(ierr); 2061 PetscStackCallBLAS("BLASgemm",BLASgemm_("T","N",&m,&n,&k,&_DOne,a->v,&a->lda,b->v,&b->lda,&_DZero,c->v,&c->lda)); 2062 PetscFunctionReturn(0); 2063 } 2064 2065 static PetscErrorCode MatGetRowMax_SeqDense(Mat A,Vec v,PetscInt idx[]) 2066 { 2067 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 2068 PetscErrorCode ierr; 2069 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,p; 2070 PetscScalar *x; 2071 MatScalar *aa = a->v; 2072 2073 PetscFunctionBegin; 2074 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2075 2076 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2077 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2078 ierr = VecGetLocalSize(v,&p);CHKERRQ(ierr); 2079 if (p != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2080 for (i=0; i<m; i++) { 2081 x[i] = aa[i]; if (idx) idx[i] = 0; 2082 for (j=1; j<n; j++) { 2083 if (PetscRealPart(x[i]) < PetscRealPart(aa[i+m*j])) {x[i] = aa[i + m*j]; if (idx) idx[i] = j;} 2084 } 2085 } 2086 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2087 PetscFunctionReturn(0); 2088 } 2089 2090 static PetscErrorCode MatGetRowMaxAbs_SeqDense(Mat A,Vec v,PetscInt idx[]) 2091 { 2092 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 2093 PetscErrorCode ierr; 2094 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,p; 2095 PetscScalar *x; 2096 PetscReal atmp; 2097 MatScalar *aa = a->v; 2098 2099 PetscFunctionBegin; 2100 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2101 2102 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2103 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2104 ierr = VecGetLocalSize(v,&p);CHKERRQ(ierr); 2105 if (p != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2106 for (i=0; i<m; i++) { 2107 x[i] = PetscAbsScalar(aa[i]); 2108 for (j=1; j<n; j++) { 2109 atmp = PetscAbsScalar(aa[i+m*j]); 2110 if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = j;} 2111 } 2112 } 2113 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2114 PetscFunctionReturn(0); 2115 } 2116 2117 static PetscErrorCode MatGetRowMin_SeqDense(Mat A,Vec v,PetscInt idx[]) 2118 { 2119 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 2120 PetscErrorCode ierr; 2121 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,p; 2122 PetscScalar *x; 2123 MatScalar *aa = a->v; 2124 2125 PetscFunctionBegin; 2126 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2127 2128 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2129 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2130 ierr = VecGetLocalSize(v,&p);CHKERRQ(ierr); 2131 if (p != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2132 for (i=0; i<m; i++) { 2133 x[i] = aa[i]; if (idx) idx[i] = 0; 2134 for (j=1; j<n; j++) { 2135 if (PetscRealPart(x[i]) > PetscRealPart(aa[i+m*j])) {x[i] = aa[i + m*j]; if (idx) idx[i] = j;} 2136 } 2137 } 2138 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2139 PetscFunctionReturn(0); 2140 } 2141 2142 static PetscErrorCode MatGetColumnVector_SeqDense(Mat A,Vec v,PetscInt col) 2143 { 2144 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 2145 PetscErrorCode ierr; 2146 PetscScalar *x; 2147 2148 PetscFunctionBegin; 2149 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2150 2151 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2152 ierr = PetscMemcpy(x,a->v+col*a->lda,A->rmap->n*sizeof(PetscScalar));CHKERRQ(ierr); 2153 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2154 PetscFunctionReturn(0); 2155 } 2156 2157 2158 PetscErrorCode MatGetColumnNorms_SeqDense(Mat A,NormType type,PetscReal *norms) 2159 { 2160 PetscErrorCode ierr; 2161 PetscInt i,j,m,n; 2162 PetscScalar *a; 2163 2164 PetscFunctionBegin; 2165 ierr = MatGetSize(A,&m,&n);CHKERRQ(ierr); 2166 ierr = PetscMemzero(norms,n*sizeof(PetscReal));CHKERRQ(ierr); 2167 ierr = MatDenseGetArray(A,&a);CHKERRQ(ierr); 2168 if (type == NORM_2) { 2169 for (i=0; i<n; i++) { 2170 for (j=0; j<m; j++) { 2171 norms[i] += PetscAbsScalar(a[j]*a[j]); 2172 } 2173 a += m; 2174 } 2175 } else if (type == NORM_1) { 2176 for (i=0; i<n; i++) { 2177 for (j=0; j<m; j++) { 2178 norms[i] += PetscAbsScalar(a[j]); 2179 } 2180 a += m; 2181 } 2182 } else if (type == NORM_INFINITY) { 2183 for (i=0; i<n; i++) { 2184 for (j=0; j<m; j++) { 2185 norms[i] = PetscMax(PetscAbsScalar(a[j]),norms[i]); 2186 } 2187 a += m; 2188 } 2189 } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType"); 2190 ierr = MatDenseRestoreArray(A,&a);CHKERRQ(ierr); 2191 if (type == NORM_2) { 2192 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 2193 } 2194 PetscFunctionReturn(0); 2195 } 2196 2197 static PetscErrorCode MatSetRandom_SeqDense(Mat x,PetscRandom rctx) 2198 { 2199 PetscErrorCode ierr; 2200 PetscScalar *a; 2201 PetscInt m,n,i; 2202 2203 PetscFunctionBegin; 2204 ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); 2205 ierr = MatDenseGetArray(x,&a);CHKERRQ(ierr); 2206 for (i=0; i<m*n; i++) { 2207 ierr = PetscRandomGetValue(rctx,a+i);CHKERRQ(ierr); 2208 } 2209 ierr = MatDenseRestoreArray(x,&a);CHKERRQ(ierr); 2210 PetscFunctionReturn(0); 2211 } 2212 2213 static PetscErrorCode MatMissingDiagonal_SeqDense(Mat A,PetscBool *missing,PetscInt *d) 2214 { 2215 PetscFunctionBegin; 2216 *missing = PETSC_FALSE; 2217 PetscFunctionReturn(0); 2218 } 2219 2220 2221 /* -------------------------------------------------------------------*/ 2222 static struct _MatOps MatOps_Values = { MatSetValues_SeqDense, 2223 MatGetRow_SeqDense, 2224 MatRestoreRow_SeqDense, 2225 MatMult_SeqDense, 2226 /* 4*/ MatMultAdd_SeqDense, 2227 MatMultTranspose_SeqDense, 2228 MatMultTransposeAdd_SeqDense, 2229 0, 2230 0, 2231 0, 2232 /* 10*/ 0, 2233 MatLUFactor_SeqDense, 2234 MatCholeskyFactor_SeqDense, 2235 MatSOR_SeqDense, 2236 MatTranspose_SeqDense, 2237 /* 15*/ MatGetInfo_SeqDense, 2238 MatEqual_SeqDense, 2239 MatGetDiagonal_SeqDense, 2240 MatDiagonalScale_SeqDense, 2241 MatNorm_SeqDense, 2242 /* 20*/ MatAssemblyBegin_SeqDense, 2243 MatAssemblyEnd_SeqDense, 2244 MatSetOption_SeqDense, 2245 MatZeroEntries_SeqDense, 2246 /* 24*/ MatZeroRows_SeqDense, 2247 0, 2248 0, 2249 0, 2250 0, 2251 /* 29*/ MatSetUp_SeqDense, 2252 0, 2253 0, 2254 0, 2255 0, 2256 /* 34*/ MatDuplicate_SeqDense, 2257 0, 2258 0, 2259 0, 2260 0, 2261 /* 39*/ MatAXPY_SeqDense, 2262 MatCreateSubMatrices_SeqDense, 2263 0, 2264 MatGetValues_SeqDense, 2265 MatCopy_SeqDense, 2266 /* 44*/ MatGetRowMax_SeqDense, 2267 MatScale_SeqDense, 2268 MatShift_Basic, 2269 0, 2270 MatZeroRowsColumns_SeqDense, 2271 /* 49*/ MatSetRandom_SeqDense, 2272 0, 2273 0, 2274 0, 2275 0, 2276 /* 54*/ 0, 2277 0, 2278 0, 2279 0, 2280 0, 2281 /* 59*/ 0, 2282 MatDestroy_SeqDense, 2283 MatView_SeqDense, 2284 0, 2285 0, 2286 /* 64*/ 0, 2287 0, 2288 0, 2289 0, 2290 0, 2291 /* 69*/ MatGetRowMaxAbs_SeqDense, 2292 0, 2293 0, 2294 0, 2295 0, 2296 /* 74*/ 0, 2297 0, 2298 0, 2299 0, 2300 0, 2301 /* 79*/ 0, 2302 0, 2303 0, 2304 0, 2305 /* 83*/ MatLoad_SeqDense, 2306 0, 2307 MatIsHermitian_SeqDense, 2308 0, 2309 0, 2310 0, 2311 /* 89*/ MatMatMult_SeqDense_SeqDense, 2312 MatMatMultSymbolic_SeqDense_SeqDense, 2313 MatMatMultNumeric_SeqDense_SeqDense, 2314 MatPtAP_SeqDense_SeqDense, 2315 MatPtAPSymbolic_SeqDense_SeqDense, 2316 /* 94*/ MatPtAPNumeric_SeqDense_SeqDense, 2317 MatMatTransposeMult_SeqDense_SeqDense, 2318 MatMatTransposeMultSymbolic_SeqDense_SeqDense, 2319 MatMatTransposeMultNumeric_SeqDense_SeqDense, 2320 0, 2321 /* 99*/ 0, 2322 0, 2323 0, 2324 MatConjugate_SeqDense, 2325 0, 2326 /*104*/ 0, 2327 MatRealPart_SeqDense, 2328 MatImaginaryPart_SeqDense, 2329 0, 2330 0, 2331 /*109*/ 0, 2332 0, 2333 MatGetRowMin_SeqDense, 2334 MatGetColumnVector_SeqDense, 2335 MatMissingDiagonal_SeqDense, 2336 /*114*/ 0, 2337 0, 2338 0, 2339 0, 2340 0, 2341 /*119*/ 0, 2342 0, 2343 0, 2344 0, 2345 0, 2346 /*124*/ 0, 2347 MatGetColumnNorms_SeqDense, 2348 0, 2349 0, 2350 0, 2351 /*129*/ 0, 2352 MatTransposeMatMult_SeqDense_SeqDense, 2353 MatTransposeMatMultSymbolic_SeqDense_SeqDense, 2354 MatTransposeMatMultNumeric_SeqDense_SeqDense, 2355 0, 2356 /*134*/ 0, 2357 0, 2358 0, 2359 0, 2360 0, 2361 /*139*/ 0, 2362 0, 2363 0 2364 }; 2365 2366 /*@C 2367 MatCreateSeqDense - Creates a sequential dense matrix that 2368 is stored in column major order (the usual Fortran 77 manner). Many 2369 of the matrix operations use the BLAS and LAPACK routines. 2370 2371 Collective on MPI_Comm 2372 2373 Input Parameters: 2374 + comm - MPI communicator, set to PETSC_COMM_SELF 2375 . m - number of rows 2376 . n - number of columns 2377 - data - optional location of matrix data in column major order. Set data=NULL for PETSc 2378 to control all matrix memory allocation. 2379 2380 Output Parameter: 2381 . A - the matrix 2382 2383 Notes: 2384 The data input variable is intended primarily for Fortran programmers 2385 who wish to allocate their own matrix memory space. Most users should 2386 set data=NULL. 2387 2388 Level: intermediate 2389 2390 .keywords: dense, matrix, LAPACK, BLAS 2391 2392 .seealso: MatCreate(), MatCreateDense(), MatSetValues() 2393 @*/ 2394 PetscErrorCode MatCreateSeqDense(MPI_Comm comm,PetscInt m,PetscInt n,PetscScalar *data,Mat *A) 2395 { 2396 PetscErrorCode ierr; 2397 2398 PetscFunctionBegin; 2399 ierr = MatCreate(comm,A);CHKERRQ(ierr); 2400 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 2401 ierr = MatSetType(*A,MATSEQDENSE);CHKERRQ(ierr); 2402 ierr = MatSeqDenseSetPreallocation(*A,data);CHKERRQ(ierr); 2403 PetscFunctionReturn(0); 2404 } 2405 2406 /*@C 2407 MatSeqDenseSetPreallocation - Sets the array used for storing the matrix elements 2408 2409 Collective on MPI_Comm 2410 2411 Input Parameters: 2412 + B - the matrix 2413 - data - the array (or NULL) 2414 2415 Notes: 2416 The data input variable is intended primarily for Fortran programmers 2417 who wish to allocate their own matrix memory space. Most users should 2418 need not call this routine. 2419 2420 Level: intermediate 2421 2422 .keywords: dense, matrix, LAPACK, BLAS 2423 2424 .seealso: MatCreate(), MatCreateDense(), MatSetValues(), MatSeqDenseSetLDA() 2425 2426 @*/ 2427 PetscErrorCode MatSeqDenseSetPreallocation(Mat B,PetscScalar data[]) 2428 { 2429 PetscErrorCode ierr; 2430 2431 PetscFunctionBegin; 2432 ierr = PetscTryMethod(B,"MatSeqDenseSetPreallocation_C",(Mat,PetscScalar[]),(B,data));CHKERRQ(ierr); 2433 PetscFunctionReturn(0); 2434 } 2435 2436 PetscErrorCode MatSeqDenseSetPreallocation_SeqDense(Mat B,PetscScalar *data) 2437 { 2438 Mat_SeqDense *b; 2439 PetscErrorCode ierr; 2440 2441 PetscFunctionBegin; 2442 B->preallocated = PETSC_TRUE; 2443 2444 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2445 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2446 2447 b = (Mat_SeqDense*)B->data; 2448 b->Mmax = B->rmap->n; 2449 b->Nmax = B->cmap->n; 2450 if (b->lda <= 0 || b->changelda) b->lda = B->rmap->n; 2451 2452 ierr = PetscIntMultError(b->lda,b->Nmax,NULL);CHKERRQ(ierr); 2453 if (!data) { /* petsc-allocated storage */ 2454 if (!b->user_alloc) { ierr = PetscFree(b->v);CHKERRQ(ierr); } 2455 ierr = PetscCalloc1((size_t)b->lda*b->Nmax,&b->v);CHKERRQ(ierr); 2456 ierr = PetscLogObjectMemory((PetscObject)B,b->lda*b->Nmax*sizeof(PetscScalar));CHKERRQ(ierr); 2457 2458 b->user_alloc = PETSC_FALSE; 2459 } else { /* user-allocated storage */ 2460 if (!b->user_alloc) { ierr = PetscFree(b->v);CHKERRQ(ierr); } 2461 b->v = data; 2462 b->user_alloc = PETSC_TRUE; 2463 } 2464 B->assembled = PETSC_TRUE; 2465 PetscFunctionReturn(0); 2466 } 2467 2468 #if defined(PETSC_HAVE_ELEMENTAL) 2469 PETSC_INTERN PetscErrorCode MatConvert_SeqDense_Elemental(Mat A, MatType newtype,MatReuse reuse,Mat *newmat) 2470 { 2471 Mat mat_elemental; 2472 PetscErrorCode ierr; 2473 PetscScalar *array,*v_colwise; 2474 PetscInt M=A->rmap->N,N=A->cmap->N,i,j,k,*rows,*cols; 2475 2476 PetscFunctionBegin; 2477 ierr = PetscMalloc3(M*N,&v_colwise,M,&rows,N,&cols);CHKERRQ(ierr); 2478 ierr = MatDenseGetArray(A,&array);CHKERRQ(ierr); 2479 /* convert column-wise array into row-wise v_colwise, see MatSetValues_Elemental() */ 2480 k = 0; 2481 for (j=0; j<N; j++) { 2482 cols[j] = j; 2483 for (i=0; i<M; i++) { 2484 v_colwise[j*M+i] = array[k++]; 2485 } 2486 } 2487 for (i=0; i<M; i++) { 2488 rows[i] = i; 2489 } 2490 ierr = MatDenseRestoreArray(A,&array);CHKERRQ(ierr); 2491 2492 ierr = MatCreate(PetscObjectComm((PetscObject)A), &mat_elemental);CHKERRQ(ierr); 2493 ierr = MatSetSizes(mat_elemental,PETSC_DECIDE,PETSC_DECIDE,M,N);CHKERRQ(ierr); 2494 ierr = MatSetType(mat_elemental,MATELEMENTAL);CHKERRQ(ierr); 2495 ierr = MatSetUp(mat_elemental);CHKERRQ(ierr); 2496 2497 /* PETSc-Elemental interaface uses axpy for setting off-processor entries, only ADD_VALUES is allowed */ 2498 ierr = MatSetValues(mat_elemental,M,rows,N,cols,v_colwise,ADD_VALUES);CHKERRQ(ierr); 2499 ierr = MatAssemblyBegin(mat_elemental, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2500 ierr = MatAssemblyEnd(mat_elemental, MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2501 ierr = PetscFree3(v_colwise,rows,cols);CHKERRQ(ierr); 2502 2503 if (reuse == MAT_INPLACE_MATRIX) { 2504 ierr = MatHeaderReplace(A,&mat_elemental);CHKERRQ(ierr); 2505 } else { 2506 *newmat = mat_elemental; 2507 } 2508 PetscFunctionReturn(0); 2509 } 2510 #endif 2511 2512 /*@C 2513 MatSeqDenseSetLDA - Declare the leading dimension of the user-provided array 2514 2515 Input parameter: 2516 + A - the matrix 2517 - lda - the leading dimension 2518 2519 Notes: 2520 This routine is to be used in conjunction with MatSeqDenseSetPreallocation(); 2521 it asserts that the preallocation has a leading dimension (the LDA parameter 2522 of Blas and Lapack fame) larger than M, the first dimension of the matrix. 2523 2524 Level: intermediate 2525 2526 .keywords: dense, matrix, LAPACK, BLAS 2527 2528 .seealso: MatCreate(), MatCreateSeqDense(), MatSeqDenseSetPreallocation(), MatSetMaximumSize() 2529 2530 @*/ 2531 PetscErrorCode MatSeqDenseSetLDA(Mat B,PetscInt lda) 2532 { 2533 Mat_SeqDense *b = (Mat_SeqDense*)B->data; 2534 2535 PetscFunctionBegin; 2536 if (lda < B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"LDA %D must be at least matrix dimension %D",lda,B->rmap->n); 2537 b->lda = lda; 2538 b->changelda = PETSC_FALSE; 2539 b->Mmax = PetscMax(b->Mmax,lda); 2540 PetscFunctionReturn(0); 2541 } 2542 2543 /*MC 2544 MATSEQDENSE - MATSEQDENSE = "seqdense" - A matrix type to be used for sequential dense matrices. 2545 2546 Options Database Keys: 2547 . -mat_type seqdense - sets the matrix type to "seqdense" during a call to MatSetFromOptions() 2548 2549 Level: beginner 2550 2551 .seealso: MatCreateSeqDense() 2552 2553 M*/ 2554 2555 PETSC_EXTERN PetscErrorCode MatCreate_SeqDense(Mat B) 2556 { 2557 Mat_SeqDense *b; 2558 PetscErrorCode ierr; 2559 PetscMPIInt size; 2560 2561 PetscFunctionBegin; 2562 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 2563 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Comm must be of size 1"); 2564 2565 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 2566 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 2567 B->data = (void*)b; 2568 2569 b->roworiented = PETSC_TRUE; 2570 2571 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDenseGetArray_C",MatDenseGetArray_SeqDense);CHKERRQ(ierr); 2572 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDensePlaceArray_C",MatDensePlaceArray_SeqDense);CHKERRQ(ierr); 2573 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDenseResetArray_C",MatDenseResetArray_SeqDense);CHKERRQ(ierr); 2574 ierr = PetscObjectComposeFunction((PetscObject)B,"MatDenseRestoreArray_C",MatDenseRestoreArray_SeqDense);CHKERRQ(ierr); 2575 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqdense_seqaij_C",MatConvert_SeqDense_SeqAIJ);CHKERRQ(ierr); 2576 #if defined(PETSC_HAVE_ELEMENTAL) 2577 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqdense_elemental_C",MatConvert_SeqDense_Elemental);CHKERRQ(ierr); 2578 #endif 2579 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqDenseSetPreallocation_C",MatSeqDenseSetPreallocation_SeqDense);CHKERRQ(ierr); 2580 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqaij_seqdense_C",MatMatMult_SeqAIJ_SeqDense);CHKERRQ(ierr); 2581 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqaij_seqdense_C",MatMatMultSymbolic_SeqAIJ_SeqDense);CHKERRQ(ierr); 2582 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqaij_seqdense_C",MatMatMultNumeric_SeqAIJ_SeqDense);CHKERRQ(ierr); 2583 ierr = PetscObjectComposeFunction((PetscObject)B,"MatPtAP_seqaij_seqdense_C",MatPtAP_SeqDense_SeqDense);CHKERRQ(ierr); 2584 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqaijperm_seqdense_C",MatMatMult_SeqAIJ_SeqDense);CHKERRQ(ierr); 2585 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqaijperm_seqdense_C",MatMatMultSymbolic_SeqAIJ_SeqDense);CHKERRQ(ierr); 2586 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqaijperm_seqdense_C",MatMatMultNumeric_SeqAIJ_SeqDense);CHKERRQ(ierr); 2587 ierr = PetscObjectComposeFunction((PetscObject)B,"MatPtAP_seqaijperm_seqdense_C",MatPtAP_SeqDense_SeqDense);CHKERRQ(ierr); 2588 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqaijmkl_seqdense_C",MatMatMult_SeqAIJ_SeqDense);CHKERRQ(ierr); 2589 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqaijmkl_seqdense_C",MatMatMultSymbolic_SeqAIJ_SeqDense);CHKERRQ(ierr); 2590 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqaijmkl_seqdense_C",MatMatMultNumeric_SeqAIJ_SeqDense);CHKERRQ(ierr); 2591 ierr = PetscObjectComposeFunction((PetscObject)B,"MatPtAP_seqaijmkl_seqdense_C",MatPtAP_SeqDense_SeqDense);CHKERRQ(ierr); 2592 2593 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMult_seqaij_seqdense_C",MatTransposeMatMult_SeqAIJ_SeqDense);CHKERRQ(ierr); 2594 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultSymbolic_seqaij_seqdense_C",MatTransposeMatMultSymbolic_SeqAIJ_SeqDense);CHKERRQ(ierr); 2595 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultNumeric_seqaij_seqdense_C",MatTransposeMatMultNumeric_SeqAIJ_SeqDense);CHKERRQ(ierr); 2596 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMult_seqaijperm_seqdense_C",MatTransposeMatMult_SeqAIJ_SeqDense);CHKERRQ(ierr); 2597 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultSymbolic_seqaijperm_seqdense_C",MatTransposeMatMultSymbolic_SeqAIJ_SeqDense);CHKERRQ(ierr); 2598 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultNumeric_seqaijperm_seqdense_C",MatTransposeMatMultNumeric_SeqAIJ_SeqDense);CHKERRQ(ierr); 2599 2600 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMult_seqaijmkl_seqdense_C",MatTransposeMatMult_SeqAIJ_SeqDense);CHKERRQ(ierr); 2601 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultSymbolic_seqaijmkl_seqdense_C",MatTransposeMatMultSymbolic_SeqAIJ_SeqDense);CHKERRQ(ierr); 2602 ierr = PetscObjectComposeFunction((PetscObject)B,"MatTransposeMatMultNumeric_seqaijmkl_seqdense_C",MatTransposeMatMultNumeric_SeqAIJ_SeqDense);CHKERRQ(ierr); 2603 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQDENSE);CHKERRQ(ierr); 2604 PetscFunctionReturn(0); 2605 } 2606